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Please answer each of the following questions to help you self-assess your understanding of "Chapter 5: Sampling" (Remler & Van Ryzin, 2010)

1. (OPTIONAL) Your email address This question requires a valid email address.

2. Please Match the Term to Its Definition *This question is required.

Space Cell

The extent to which the results generalize to a wider group or reality, external to the study. Another term for generalizability.

A subset of a population (sample) chosen at random.

A sample consisting of volunteers.

Process of selecting people or elements from a population for inclusion in a research study.

A method for pooling together multiple smaller studies to get a much bigger, combined study.

Sample chosen based on probability, at random on some level, which makes the sample representative.

A subset of people or elements selected from a population.

The population the study aims to investigate.

A nonprobability sample that was chosen for convenience and that may be biased.

Repeating a study with a different sample, in a different place, time period, or policy context, or with a different study design.

External Validity

The extent to which the results generalize to a wider group or reality, external to the study. Another term for generalizability.

A subset of a population (sample) chosen at random.

A sample consisting of volunteers.

Process of selecting people or elements from a population for inclusion in a research study.

A method for pooling together multiple smaller studies to get a much bigger, combined study.

Sample chosen based on probability, at random on some level, which makes the sample representative.

A subset of people or elements selected from a population.

The population the study aims to investigate.

A nonprobability sample that was chosen for convenience and that may be biased.

Repeating a study with a different sample, in a different place, time period, or policy context, or with a different study design.

Convenience Sample

The extent to which the results generalize to a wider group or reality, external to the study. Another term for generalizability.

A subset of a population (sample) chosen at random.

A sample consisting of volunteers.

Process of selecting people or elements from a population for inclusion in a research study.

A method for pooling together multiple smaller studies to get a much bigger, combined study.

Sample chosen based on probability, at random on some level, which makes the sample representative.

A subset of people or elements selected from a population.

The population the study aims to investigate.

A nonprobability sample that was chosen for convenience and that may be biased.

Repeating a study with a different sample, in a different place, time period, or policy context, or with a different study design.

Random Sample

The extent to which the results generalize to a wider group or reality, external to the study. Another term for generalizability.

A subset of a population (sample) chosen at random.

A sample consisting of volunteers.

Process of selecting people or elements from a population for inclusion in a research study.

A method for pooling together multiple smaller studies to get a much bigger, combined study.

Sample chosen based on probability, at random on some level, which makes the sample representative.

A subset of people or elements selected from a population.

The population the study aims to investigate.

A nonprobability sample that was chosen for convenience and that may be biased.

Repeating a study with a different sample, in a different place, time period, or policy context, or with a different study design.

Meta-Analysis *This question is required

The extent to which the results generalize to a wider group or reality, external to the study. Another term for generalizability.

A subset of a population (sample) chosen at random.

A sample consisting of volunteers.

Process of selecting people or elements from a population for inclusion in a research study.

A method for pooling together multiple smaller studies to get a much bigger, combined study.

Sample chosen based on probability, at random on some level, which makes the sample representative.

A subset of people or elements selected from a population.

The population the study aims to investigate.

A nonprobability sample that was chosen for convenience and that may be biased.

Repeating a study with a different sample, in a different place, time period, or policy context, or with a different study design.

Voluntary Sample

The extent to which the results generalize to a wider group or reality, external to the study. Another term for generalizability.

A subset of a population (sample) chosen at random.

A sample consisting of volunteers.

Process of selecting people or elements from a population for inclusion in a research study.

A method for pooling together multiple smaller studies to get a much bigger, combined study.

Sample chosen based on probability, at random on some level, which makes the sample representative.

A subset of people or elements selected from a population.

The population the study aims to investigate.

A nonprobability sample that was chosen for convenience and that may be biased.

Repeating a study with a different sample, in a different place, time period, or policy context, or with a different study design.

Sample *This question is required

The extent to which the results generalize to a wider group or reality, external to the study. Another term for generalizability.

A subset of a population (sample) chosen at random.

A sample consisting of volunteers.

Process of selecting people or elements from a population for inclusion in a research study.

A method for pooling together multiple smaller studies to get a much bigger, combined study.

Sample chosen based on probability, at random on some level, which makes the sample representative.

A subset of people or elements selected from a population.

The population the study aims to investigate.

A nonprobability sample that was chosen for convenience and that may be biased.

Repeating a study with a different sample, in a different place, time period, or policy context, or with a different study design.

Replication *This question is required

The extent to which the results generalize to a wider group or reality, external to the study. Another term for generalizability.

A subset of a population (sample) chosen at random.

A sample consisting of volunteers.

Process of selecting people or elements from a population for inclusion in a research study.

A method for pooling together multiple smaller studies to get a much bigger, combined study.

Sample chosen based on probability, at random on some level, which makes the sample representative.

A subset of people or elements selected from a population.

The population the study aims to investigate.

A nonprobability sample that was chosen for convenience and that may be biased.

Repeating a study with a different sample, in a different place, time period, or policy context, or with a different study design.

Sampling

The extent to which the results generalize to a wider group or reality, external to the study. Another term for generalizability.

A subset of a population (sample) chosen at random.

A sample consisting of volunteers.

Process of selecting people or elements from a population for inclusion in a research study.

A method for pooling together multiple smaller studies to get a much bigger, combined study.

Sample chosen based on probability, at random on some level, which makes the sample representative.

A subset of people or elements selected from a population.

The population the study aims to investigate.

A nonprobability sample that was chosen for convenience and that may be biased.

Repeating a study with a different sample, in a different place, time period, or policy context, or with a different study design.

Population of Interest

The extent to which the results generalize to a wider group or reality, external to the study. Another term for generalizability.

A subset of a population (sample) chosen at random.

A sample consisting of volunteers.

Process of selecting people or elements from a population for inclusion in a research study.

A method for pooling together multiple smaller studies to get a much bigger, combined study.

Sample chosen based on probability, at random on some level, which makes the sample representative.

A subset of people or elements selected from a population.

The population the study aims to investigate.

A nonprobability sample that was chosen for convenience and that may be biased.

Repeating a study with a different sample, in a different place, time period, or policy context, or with a different study design.

Probability Sample

The extent to which the results generalize to a wider group or reality, external to the study. Another term for generalizability.

A subset of a population (sample) chosen at random.

A sample consisting of volunteers.

Process of selecting people or elements from a population for inclusion in a research study.

A method for pooling together multiple smaller studies to get a much bigger, combined study.

Sample chosen based on probability, at random on some level, which makes the sample representative.

A subset of people or elements selected from a population.

The population the study aims to investigate.

A nonprobability sample that was chosen for convenience and that may be biased.

Repeating a study with a different sample, in a different place, time period, or policy context, or with a different study design.

3. Please Match the Term to Its Definition *This question is required.

Space Cell

Share who cooperate with a survey request from among those contacted.

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

Using samples to learn about the population, or using evidence to identify a causal relationship.

The list of enumeration of the population from which the sample is taken.

Bias in survey that occurs when members of the sampling frame are systematically different from the target population in a way related to the measures.

Share who are reached from those sampled from the sampling frame.

A telephone survey method that gives both listed and unlisted numbers an equal chance of being selected by replacing random digits at the ends of listed residential telephone numbers.

Share who respond to a survey from among those sampled from a sampling frame.

Random Digit Dialing (RDD)

Share who cooperate with a survey request from among those contacted.

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

Using samples to learn about the population, or using evidence to identify a causal relationship.

The list of enumeration of the population from which the sample is taken.

Bias in survey that occurs when members of the sampling frame are systematically different from the target population in a way related to the measures.

Share who are reached from those sampled from the sampling frame.

A telephone survey method that gives both listed and unlisted numbers an equal chance of being selected by replacing random digits at the ends of listed residential telephone numbers.

Share who respond to a survey from among those sampled from a sampling frame.

Response Rate

Share who cooperate with a survey request from among those contacted.

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

Using samples to learn about the population, or using evidence to identify a causal relationship.

The list of enumeration of the population from which the sample is taken.

Bias in survey that occurs when members of the sampling frame are systematically different from the target population in a way related to the measures.

Share who are reached from those sampled from the sampling frame.

A telephone survey method that gives both listed and unlisted numbers an equal chance of being selected by replacing random digits at the ends of listed residential telephone numbers.

Share who respond to a survey from among those sampled from a sampling frame.

Coverage Bias

Share who cooperate with a survey request from among those contacted.

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

Using samples to learn about the population, or using evidence to identify a causal relationship.

The list of enumeration of the population from which the sample is taken.

Bias in survey that occurs when members of the sampling frame are systematically different from the target population in a way related to the measures.

Share who are reached from those sampled from the sampling frame.

A telephone survey method that gives both listed and unlisted numbers an equal chance of being selected by replacing random digits at the ends of listed residential telephone numbers.

Share who respond to a survey from among those sampled from a sampling frame.

Universe

Share who cooperate with a survey request from among those contacted.

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

Using samples to learn about the population, or using evidence to identify a causal relationship.

The list of enumeration of the population from which the sample is taken.

Bias in survey that occurs when members of the sampling frame are systematically different from the target population in a way related to the measures.

Share who are reached from those sampled from the sampling frame.

A telephone survey method that gives both listed and unlisted numbers an equal chance of being selected by replacing random digits at the ends of listed residential telephone numbers.

Share who respond to a survey from among those sampled from a sampling frame.

Inference

Share who cooperate with a survey request from among those contacted.

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

Using samples to learn about the population, or using evidence to identify a causal relationship.

The list of enumeration of the population from which the sample is taken.

Bias in survey that occurs when members of the sampling frame are systematically different from the target population in a way related to the measures.

Share who are reached from those sampled from the sampling frame.

A telephone survey method that gives both listed and unlisted numbers an equal chance of being selected by replacing random digits at the ends of listed residential telephone numbers.

Share who respond to a survey from among those sampled from a sampling frame.

Sampling Frame

Share who cooperate with a survey request from among those contacted.

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

Using samples to learn about the population, or using evidence to identify a causal relationship.

The list of enumeration of the population from which the sample is taken.

Bias in survey that occurs when members of the sampling frame are systematically different from the target population in a way related to the measures.

Share who are reached from those sampled from the sampling frame.

A telephone survey method that gives both listed and unlisted numbers an equal chance of being selected by replacing random digits at the ends of listed residential telephone numbers.

Share who respond to a survey from among those sampled from a sampling frame.

Cooperation Rate *This question is required

Share who cooperate with a survey request from among those contacted.

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

Using samples to learn about the population, or using evidence to identify a causal relationship.

The list of enumeration of the population from which the sample is taken.

Bias in survey that occurs when members of the sampling frame are systematically different from the target population in a way related to the measures.

Share who are reached from those sampled from the sampling frame.

A telephone survey method that gives both listed and unlisted numbers an equal chance of being selected by replacing random digits at the ends of listed residential telephone numbers.

Share who respond to a survey from among those sampled from a sampling frame.

Contact Rate *This question is required

Share who cooperate with a survey request from among those contacted.

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

Using samples to learn about the population, or using evidence to identify a causal relationship.

The list of enumeration of the population from which the sample is taken.

Bias in survey that occurs when members of the sampling frame are systematically different from the target population in a way related to the measures.

Share who are reached from those sampled from the sampling frame.

A telephone survey method that gives both listed and unlisted numbers an equal chance of being selected by replacing random digits at the ends of listed residential telephone numbers.

Share who respond to a survey from among those sampled from a sampling frame.

Propensity to Respond *This question is required

Share who cooperate with a survey request from among those contacted.

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

Using samples to learn about the population, or using evidence to identify a causal relationship.

The list of enumeration of the population from which the sample is taken.

Bias in survey that occurs when members of the sampling frame are systematically different from the target population in a way related to the measures.

Share who are reached from those sampled from the sampling frame.

A telephone survey method that gives both listed and unlisted numbers an equal chance of being selected by replacing random digits at the ends of listed residential telephone numbers.

Share who respond to a survey from among those sampled from a sampling frame.

Census

Share who cooperate with a survey request from among those contacted.

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

Using samples to learn about the population, or using evidence to identify a causal relationship.

The list of enumeration of the population from which the sample is taken.

Bias in survey that occurs when members of the sampling frame are systematically different from the target population in a way related to the measures.

Share who are reached from those sampled from the sampling frame.

A telephone survey method that gives both listed and unlisted numbers an equal chance of being selected by replacing random digits at the ends of listed residential telephone numbers.

Share who respond to a survey from among those sampled from a sampling frame.

4. Please Match the Term to Its Definition *This question is required.

Space Cell

Bias in a study that occurs when volunteers differ from a more representative sample of the population in ways that influence the findings of the study.

The distribution of statistics estimated from many repeated samples.

Method of sampling based on respondent contacts, like snowball sampling, but with a statistical foundation.

Method of sampling or finding study subjects in which interviewees are asked to refer people they know to the researcher for inclusion in the sample.

Variability in sample statistics, across different samples, due to random chance of who ends up in a sample.

Bias in survey results that occurs when those who do not respond are systematically different from those who do respond in a way related to the measures.

Error in sample statistics due to random chance of who ends up in a sample.

A theoretical distribution that is bell-shaped, symmetrical, and has many useful properties in statistics.

Selecting of people (or elements) from a population in such a way that each individual has an equal chance, or probability, of selection.

Choosing from the sampling frame at random.

Volunteer Bias

Bias in a study that occurs when volunteers differ from a more representative sample of the population in ways that influence the findings of the study.

The distribution of statistics estimated from many repeated samples.

Method of sampling based on respondent contacts, like snowball sampling, but with a statistical foundation.

Method of sampling or finding study subjects in which interviewees are asked to refer people they know to the researcher for inclusion in the sample.

Variability in sample statistics, across different samples, due to random chance of who ends up in a sample.

Bias in survey results that occurs when those who do not respond are systematically different from those who do respond in a way related to the measures.

Error in sample statistics due to random chance of who ends up in a sample.

A theoretical distribution that is bell-shaped, symmetrical, and has many useful properties in statistics.

Selecting of people (or elements) from a population in such a way that each individual has an equal chance, or probability, of selection.

Choosing from the sampling frame at random.

Snowball Sampling

Bias in a study that occurs when volunteers differ from a more representative sample of the population in ways that influence the findings of the study.

The distribution of statistics estimated from many repeated samples.

Method of sampling based on respondent contacts, like snowball sampling, but with a statistical foundation.

Method of sampling or finding study subjects in which interviewees are asked to refer people they know to the researcher for inclusion in the sample.

Variability in sample statistics, across different samples, due to random chance of who ends up in a sample.

Bias in survey results that occurs when those who do not respond are systematically different from those who do respond in a way related to the measures.

Error in sample statistics due to random chance of who ends up in a sample.

A theoretical distribution that is bell-shaped, symmetrical, and has many useful properties in statistics.

Selecting of people (or elements) from a population in such a way that each individual has an equal chance, or probability, of selection.

Choosing from the sampling frame at random.

Simple Random Sampling

Bias in a study that occurs when volunteers differ from a more representative sample of the population in ways that influence the findings of the study.

The distribution of statistics estimated from many repeated samples.

Method of sampling based on respondent contacts, like snowball sampling, but with a statistical foundation.

Method of sampling or finding study subjects in which interviewees are asked to refer people they know to the researcher for inclusion in the sample.

Variability in sample statistics, across different samples, due to random chance of who ends up in a sample.

Bias in survey results that occurs when those who do not respond are systematically different from those who do respond in a way related to the measures.

Error in sample statistics due to random chance of who ends up in a sample.

A theoretical distribution that is bell-shaped, symmetrical, and has many useful properties in statistics.

Selecting of people (or elements) from a population in such a way that each individual has an equal chance, or probability, of selection.

Choosing from the sampling frame at random.

Random Sampling (or Probability Sampling)

Bias in a study that occurs when volunteers differ from a more representative sample of the population in ways that influence the findings of the study.

The distribution of statistics estimated from many repeated samples.

Method of sampling based on respondent contacts, like snowball sampling, but with a statistical foundation.

Method of sampling or finding study subjects in which interviewees are asked to refer people they know to the researcher for inclusion in the sample.

Variability in sample statistics, across different samples, due to random chance of who ends up in a sample.

Bias in survey results that occurs when those who do not respond are systematically different from those who do respond in a way related to the measures.

Error in sample statistics due to random chance of who ends up in a sample.

A theoretical distribution that is bell-shaped, symmetrical, and has many useful properties in statistics.

Selecting of people (or elements) from a population in such a way that each individual has an equal chance, or probability, of selection.

Choosing from the sampling frame at random.

Sampling Distribution *This question is required

Bias in a study that occurs when volunteers differ from a more representative sample of the population in ways that influence the findings of the study.

The distribution of statistics estimated from many repeated samples.

Method of sampling based on respondent contacts, like snowball sampling, but with a statistical foundation.

Method of sampling or finding study subjects in which interviewees are asked to refer people they know to the researcher for inclusion in the sample.

Variability in sample statistics, across different samples, due to random chance of who ends up in a sample.

Bias in survey results that occurs when those who do not respond are systematically different from those who do respond in a way related to the measures.

Error in sample statistics due to random chance of who ends up in a sample.

A theoretical distribution that is bell-shaped, symmetrical, and has many useful properties in statistics.

Selecting of people (or elements) from a population in such a way that each individual has an equal chance, or probability, of selection.

Choosing from the sampling frame at random.

Nonresponse Bias

Bias in a study that occurs when volunteers differ from a more representative sample of the population in ways that influence the findings of the study.

The distribution of statistics estimated from many repeated samples.

Method of sampling based on respondent contacts, like snowball sampling, but with a statistical foundation.

Method of sampling or finding study subjects in which interviewees are asked to refer people they know to the researcher for inclusion in the sample.

Variability in sample statistics, across different samples, due to random chance of who ends up in a sample.

Bias in survey results that occurs when those who do not respond are systematically different from those who do respond in a way related to the measures.

Error in sample statistics due to random chance of who ends up in a sample.

A theoretical distribution that is bell-shaped, symmetrical, and has many useful properties in statistics.

Selecting of people (or elements) from a population in such a way that each individual has an equal chance, or probability, of selection.

Choosing from the sampling frame at random.

Normal Distribution *This question is required

Bias in a study that occurs when volunteers differ from a more representative sample of the population in ways that influence the findings of the study.

The distribution of statistics estimated from many repeated samples.

Method of sampling based on respondent contacts, like snowball sampling, but with a statistical foundation.

Method of sampling or finding study subjects in which interviewees are asked to refer people they know to the researcher for inclusion in the sample.

Variability in sample statistics, across different samples, due to random chance of who ends up in a sample.

Bias in survey results that occurs when those who do not respond are systematically different from those who do respond in a way related to the measures.

Error in sample statistics due to random chance of who ends up in a sample.

A theoretical distribution that is bell-shaped, symmetrical, and has many useful properties in statistics.

Selecting of people (or elements) from a population in such a way that each individual has an equal chance, or probability, of selection.

Choosing from the sampling frame at random.

Respondent-Driven Sampling

Bias in a study that occurs when volunteers differ from a more representative sample of the population in ways that influence the findings of the study.

The distribution of statistics estimated from many repeated samples.

Method of sampling based on respondent contacts, like snowball sampling, but with a statistical foundation.

Method of sampling or finding study subjects in which interviewees are asked to refer people they know to the researcher for inclusion in the sample.

Variability in sample statistics, across different samples, due to random chance of who ends up in a sample.

Bias in survey results that occurs when those who do not respond are systematically different from those who do respond in a way related to the measures.

Error in sample statistics due to random chance of who ends up in a sample.

A theoretical distribution that is bell-shaped, symmetrical, and has many useful properties in statistics.

Selecting of people (or elements) from a population in such a way that each individual has an equal chance, or probability, of selection.

Choosing from the sampling frame at random.

Sampling Error *This question is required

Bias in a study that occurs when volunteers differ from a more representative sample of the population in ways that influence the findings of the study.

The distribution of statistics estimated from many repeated samples.

Method of sampling based on respondent contacts, like snowball sampling, but with a statistical foundation.

Method of sampling or finding study subjects in which interviewees are asked to refer people they know to the researcher for inclusion in the sample.

Variability in sample statistics, across different samples, due to random chance of who ends up in a sample.

Bias in survey results that occurs when those who do not respond are systematically different from those who do respond in a way related to the measures.

Error in sample statistics due to random chance of who ends up in a sample.

A theoretical distribution that is bell-shaped, symmetrical, and has many useful properties in statistics.

Selecting of people (or elements) from a population in such a way that each individual has an equal chance, or probability, of selection.

Choosing from the sampling frame at random.

Sampling Variability

Bias in a study that occurs when volunteers differ from a more representative sample of the population in ways that influence the findings of the study.

The distribution of statistics estimated from many repeated samples.

Method of sampling based on respondent contacts, like snowball sampling, but with a statistical foundation.

Method of sampling or finding study subjects in which interviewees are asked to refer people they know to the researcher for inclusion in the sample.

Variability in sample statistics, across different samples, due to random chance of who ends up in a sample.

Bias in survey results that occurs when those who do not respond are systematically different from those who do respond in a way related to the measures.

Error in sample statistics due to random chance of who ends up in a sample.

A theoretical distribution that is bell-shaped, symmetrical, and has many useful properties in statistics.

Selecting of people (or elements) from a population in such a way that each individual has an equal chance, or probability, of selection.

Choosing from the sampling frame at random.

5. Please Match the Term to Its Definition *This question is required.

Space Cell

Exhaustive and mutually exclusive subgroups of a target population.

Probability sampling method in which individuals or elements are sampled at even intervals - every kth individual for some integer k.

A variation on stratified sampling in which some strata are sampled with probability greater than their population share. Also called disproportionate sampling.

The amount added to the point estimate in both directions to create the confidence interval.

A variation on stratified sampling in which some strata are sampled at different rates. Also called oversampling.

The actual data available in the sample, equal to the true sample minus those who could not be reached and those who did not agree to participate.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which a sample is drawn separately from each group - each stratum - and the population is divided into exhaustive and mutually exclusive strata.

The precision of the estimate - how good a job we expect it to do, on average.

All the people or elements originally selected from the sampling frame, regardless of whether they are contacted or respond.

Standard Error

Exhaustive and mutually exclusive subgroups of a target population.

Probability sampling method in which individuals or elements are sampled at even intervals - every kth individual for some integer k.

A variation on stratified sampling in which some strata are sampled with probability greater than their population share. Also called disproportionate sampling.

The amount added to the point estimate in both directions to create the confidence interval.

A variation on stratified sampling in which some strata are sampled at different rates. Also called oversampling.

The actual data available in the sample, equal to the true sample minus those who could not be reached and those who did not agree to participate.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which a sample is drawn separately from each group - each stratum - and the population is divided into exhaustive and mutually exclusive strata.

The precision of the estimate - how good a job we expect it to do, on average.

All the people or elements originally selected from the sampling frame, regardless of whether they are contacted or respond.

Confidence Interval

Exhaustive and mutually exclusive subgroups of a target population.

Probability sampling method in which individuals or elements are sampled at even intervals - every kth individual for some integer k.

A variation on stratified sampling in which some strata are sampled with probability greater than their population share. Also called disproportionate sampling.

The amount added to the point estimate in both directions to create the confidence interval.

A variation on stratified sampling in which some strata are sampled at different rates. Also called oversampling.

The actual data available in the sample, equal to the true sample minus those who could not be reached and those who did not agree to participate.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which a sample is drawn separately from each group - each stratum - and the population is divided into exhaustive and mutually exclusive strata.

The precision of the estimate - how good a job we expect it to do, on average.

All the people or elements originally selected from the sampling frame, regardless of whether they are contacted or respond.

Margin of Error

Exhaustive and mutually exclusive subgroups of a target population.

Probability sampling method in which individuals or elements are sampled at even intervals - every kth individual for some integer k.

A variation on stratified sampling in which some strata are sampled with probability greater than their population share. Also called disproportionate sampling.

The amount added to the point estimate in both directions to create the confidence interval.

A variation on stratified sampling in which some strata are sampled at different rates. Also called oversampling.

The actual data available in the sample, equal to the true sample minus those who could not be reached and those who did not agree to participate.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which a sample is drawn separately from each group - each stratum - and the population is divided into exhaustive and mutually exclusive strata.

The precision of the estimate - how good a job we expect it to do, on average.

All the people or elements originally selected from the sampling frame, regardless of whether they are contacted or respond.

True Sample

Exhaustive and mutually exclusive subgroups of a target population.

Probability sampling method in which individuals or elements are sampled at even intervals - every kth individual for some integer k.

A variation on stratified sampling in which some strata are sampled with probability greater than their population share. Also called disproportionate sampling.

The amount added to the point estimate in both directions to create the confidence interval.

A variation on stratified sampling in which some strata are sampled at different rates. Also called oversampling.

The actual data available in the sample, equal to the true sample minus those who could not be reached and those who did not agree to participate.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which a sample is drawn separately from each group - each stratum - and the population is divided into exhaustive and mutually exclusive strata.

The precision of the estimate - how good a job we expect it to do, on average.

All the people or elements originally selected from the sampling frame, regardless of whether they are contacted or respond.

Observed Sample

Exhaustive and mutually exclusive subgroups of a target population.

Probability sampling method in which individuals or elements are sampled at even intervals - every kth individual for some integer k.

A variation on stratified sampling in which some strata are sampled with probability greater than their population share. Also called disproportionate sampling.

The amount added to the point estimate in both directions to create the confidence interval.

A variation on stratified sampling in which some strata are sampled at different rates. Also called oversampling.

The actual data available in the sample, equal to the true sample minus those who could not be reached and those who did not agree to participate.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which a sample is drawn separately from each group - each stratum - and the population is divided into exhaustive and mutually exclusive strata.

The precision of the estimate - how good a job we expect it to do, on average.

All the people or elements originally selected from the sampling frame, regardless of whether they are contacted or respond.

Systematic Sampling

Exhaustive and mutually exclusive subgroups of a target population.

Probability sampling method in which individuals or elements are sampled at even intervals - every kth individual for some integer k.

A variation on stratified sampling in which some strata are sampled with probability greater than their population share. Also called disproportionate sampling.

The amount added to the point estimate in both directions to create the confidence interval.

A variation on stratified sampling in which some strata are sampled at different rates. Also called oversampling.

The actual data available in the sample, equal to the true sample minus those who could not be reached and those who did not agree to participate.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which a sample is drawn separately from each group - each stratum - and the population is divided into exhaustive and mutually exclusive strata.

The precision of the estimate - how good a job we expect it to do, on average.

All the people or elements originally selected from the sampling frame, regardless of whether they are contacted or respond.

Strata

Exhaustive and mutually exclusive subgroups of a target population.

Probability sampling method in which individuals or elements are sampled at even intervals - every kth individual for some integer k.

A variation on stratified sampling in which some strata are sampled with probability greater than their population share. Also called disproportionate sampling.

The amount added to the point estimate in both directions to create the confidence interval.

A variation on stratified sampling in which some strata are sampled at different rates. Also called oversampling.

The actual data available in the sample, equal to the true sample minus those who could not be reached and those who did not agree to participate.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which a sample is drawn separately from each group - each stratum - and the population is divided into exhaustive and mutually exclusive strata.

The precision of the estimate - how good a job we expect it to do, on average.

All the people or elements originally selected from the sampling frame, regardless of whether they are contacted or respond.

Stratified Sampling *This question is required

Exhaustive and mutually exclusive subgroups of a target population.

Probability sampling method in which individuals or elements are sampled at even intervals - every kth individual for some integer k.

A variation on stratified sampling in which some strata are sampled with probability greater than their population share. Also called disproportionate sampling.

The amount added to the point estimate in both directions to create the confidence interval.

A variation on stratified sampling in which some strata are sampled at different rates. Also called oversampling.

The actual data available in the sample, equal to the true sample minus those who could not be reached and those who did not agree to participate.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which a sample is drawn separately from each group - each stratum - and the population is divided into exhaustive and mutually exclusive strata.

The precision of the estimate - how good a job we expect it to do, on average.

All the people or elements originally selected from the sampling frame, regardless of whether they are contacted or respond.

Oversampling *This question is required

Exhaustive and mutually exclusive subgroups of a target population.

Probability sampling method in which individuals or elements are sampled at even intervals - every kth individual for some integer k.

A variation on stratified sampling in which some strata are sampled with probability greater than their population share. Also called disproportionate sampling.

The amount added to the point estimate in both directions to create the confidence interval.

A variation on stratified sampling in which some strata are sampled at different rates. Also called oversampling.

The actual data available in the sample, equal to the true sample minus those who could not be reached and those who did not agree to participate.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which a sample is drawn separately from each group - each stratum - and the population is divided into exhaustive and mutually exclusive strata.

The precision of the estimate - how good a job we expect it to do, on average.

All the people or elements originally selected from the sampling frame, regardless of whether they are contacted or respond.

Disproportinate Sampling *This question is required

Exhaustive and mutually exclusive subgroups of a target population.

Probability sampling method in which individuals or elements are sampled at even intervals - every kth individual for some integer k.

A variation on stratified sampling in which some strata are sampled with probability greater than their population share. Also called disproportionate sampling.

The amount added to the point estimate in both directions to create the confidence interval.

A variation on stratified sampling in which some strata are sampled at different rates. Also called oversampling.

The actual data available in the sample, equal to the true sample minus those who could not be reached and those who did not agree to participate.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which a sample is drawn separately from each group - each stratum - and the population is divided into exhaustive and mutually exclusive strata.

The precision of the estimate - how good a job we expect it to do, on average.

All the people or elements originally selected from the sampling frame, regardless of whether they are contacted or respond.

6. Please Match the Term to Its Definition *This question is required.

Space Cell

The comparable sample size from a simple random sample; it expresses the design effect (often a loss) due to complex sampling.

A probability sampling method in which more aggregated units (clusters) are sampled and then sampling occurs within the aggregates.

Adjustment of sample statistics to ensure that each stratum's share of the sample represents its share in the population. Used to correct samples that do not reflect the characteristics of the population. Also called poststratification adjustment.

Probability sampling methods that are more complex than simple random sampling, such as cluster sampling, stratified sampling, and disproportionate sampling.

Similarity of elements within a cluster. Also referred to as rho - the rate of homogeneity.

Adjustment of sample statistics to ensure that each stratum's share of the sample represents its share in the population. Used to correct samples that do not reflect the characteristics of the population. Also called poststratification weighting.

The loss of precision due to a particular complex survey sampling design.

A procedure for giving some individuals in the data more, or less, weight in the analysis. Often required when disproportionate or complex sampling is used.

A probability sampling method in which more aggregated units (clusters) are sampled before sampling individuals.

Weighting

The comparable sample size from a simple random sample; it expresses the design effect (often a loss) due to complex sampling.

A probability sampling method in which more aggregated units (clusters) are sampled and then sampling occurs within the aggregates.

Adjustment of sample statistics to ensure that each stratum's share of the sample represents its share in the population. Used to correct samples that do not reflect the characteristics of the population. Also called poststratification adjustment.

Probability sampling methods that are more complex than simple random sampling, such as cluster sampling, stratified sampling, and disproportionate sampling.

Similarity of elements within a cluster. Also referred to as rho - the rate of homogeneity.

Adjustment of sample statistics to ensure that each stratum's share of the sample represents its share in the population. Used to correct samples that do not reflect the characteristics of the population. Also called poststratification weighting.

The loss of precision due to a particular complex survey sampling design.

A procedure for giving some individuals in the data more, or less, weight in the analysis. Often required when disproportionate or complex sampling is used.

A probability sampling method in which more aggregated units (clusters) are sampled before sampling individuals.

Effective Sample Size

The comparable sample size from a simple random sample; it expresses the design effect (often a loss) due to complex sampling.

A probability sampling method in which more aggregated units (clusters) are sampled and then sampling occurs within the aggregates.

Adjustment of sample statistics to ensure that each stratum's share of the sample represents its share in the population. Used to correct samples that do not reflect the characteristics of the population. Also called poststratification adjustment.

Probability sampling methods that are more complex than simple random sampling, such as cluster sampling, stratified sampling, and disproportionate sampling.

Similarity of elements within a cluster. Also referred to as rho - the rate of homogeneity.

Adjustment of sample statistics to ensure that each stratum's share of the sample represents its share in the population. Used to correct samples that do not reflect the characteristics of the population. Also called poststratification weighting.

The loss of precision due to a particular complex survey sampling design.

A procedure for giving some individuals in the data more, or less, weight in the analysis. Often required when disproportionate or complex sampling is used.

A probability sampling method in which more aggregated units (clusters) are sampled before sampling individuals.

Poststratification Adjustment

The comparable sample size from a simple random sample; it expresses the design effect (often a loss) due to complex sampling.

A probability sampling method in which more aggregated units (clusters) are sampled and then sampling occurs within the aggregates.

Adjustment of sample statistics to ensure that each stratum's share of the sample represents its share in the population. Used to correct samples that do not reflect the characteristics of the population. Also called poststratification adjustment.

Probability sampling methods that are more complex than simple random sampling, such as cluster sampling, stratified sampling, and disproportionate sampling.

Similarity of elements within a cluster. Also referred to as rho - the rate of homogeneity.

Adjustment of sample statistics to ensure that each stratum's share of the sample represents its share in the population. Used to correct samples that do not reflect the characteristics of the population. Also called poststratification weighting.

The loss of precision due to a particular complex survey sampling design.

A procedure for giving some individuals in the data more, or less, weight in the analysis. Often required when disproportionate or complex sampling is used.

A probability sampling method in which more aggregated units (clusters) are sampled before sampling individuals.

Poststratification Weighting

The comparable sample size from a simple random sample; it expresses the design effect (often a loss) due to complex sampling.

A probability sampling method in which more aggregated units (clusters) are sampled and then sampling occurs within the aggregates.

Adjustment of sample statistics to ensure that each stratum's share of the sample represents its share in the population. Used to correct samples that do not reflect the characteristics of the population. Also called poststratification adjustment.

Probability sampling methods that are more complex than simple random sampling, such as cluster sampling, stratified sampling, and disproportionate sampling.

Similarity of elements within a cluster. Also referred to as rho - the rate of homogeneity.

Adjustment of sample statistics to ensure that each stratum's share of the sample represents its share in the population. Used to correct samples that do not reflect the characteristics of the population. Also called poststratification weighting.

The loss of precision due to a particular complex survey sampling design.

A procedure for giving some individuals in the data more, or less, weight in the analysis. Often required when disproportionate or complex sampling is used.

A probability sampling method in which more aggregated units (clusters) are sampled before sampling individuals.

Multistage Sampling

The comparable sample size from a simple random sample; it expresses the design effect (often a loss) due to complex sampling.

A probability sampling method in which more aggregated units (clusters) are sampled and then sampling occurs within the aggregates.

Adjustment of sample statistics to ensure that each stratum's share of the sample represents its share in the population. Used to correct samples that do not reflect the characteristics of the population. Also called poststratification adjustment.

Probability sampling methods that are more complex than simple random sampling, such as cluster sampling, stratified sampling, and disproportionate sampling.

Similarity of elements within a cluster. Also referred to as rho - the rate of homogeneity.

Adjustment of sample statistics to ensure that each stratum's share of the sample represents its share in the population. Used to correct samples that do not reflect the characteristics of the population. Also called poststratification weighting.

The loss of precision due to a particular complex survey sampling design.

A procedure for giving some individuals in the data more, or less, weight in the analysis. Often required when disproportionate or complex sampling is used.

A probability sampling method in which more aggregated units (clusters) are sampled before sampling individuals.

Cluster Sampling

The comparable sample size from a simple random sample; it expresses the design effect (often a loss) due to complex sampling.

A probability sampling method in which more aggregated units (clusters) are sampled and then sampling occurs within the aggregates.

Adjustment of sample statistics to ensure that each stratum's share of the sample represents its share in the population. Used to correct samples that do not reflect the characteristics of the population. Also called poststratification adjustment.

Probability sampling methods that are more complex than simple random sampling, such as cluster sampling, stratified sampling, and disproportionate sampling.

Similarity of elements within a cluster. Also referred to as rho - the rate of homogeneity.

Adjustment of sample statistics to ensure that each stratum's share of the sample represents its share in the population. Used to correct samples that do not reflect the characteristics of the population. Also called poststratification weighting.

The loss of precision due to a particular complex survey sampling design.

A procedure for giving some individuals in the data more, or less, weight in the analysis. Often required when disproportionate or complex sampling is used.

A probability sampling method in which more aggregated units (clusters) are sampled before sampling individuals.

Intraclass Correlation

The comparable sample size from a simple random sample; it expresses the design effect (often a loss) due to complex sampling.

A probability sampling method in which more aggregated units (clusters) are sampled and then sampling occurs within the aggregates.

Adjustment of sample statistics to ensure that each stratum's share of the sample represents its share in the population. Used to correct samples that do not reflect the characteristics of the population. Also called poststratification adjustment.

Probability sampling methods that are more complex than simple random sampling, such as cluster sampling, stratified sampling, and disproportionate sampling.

Similarity of elements within a cluster. Also referred to as rho - the rate of homogeneity.

Adjustment of sample statistics to ensure that each stratum's share of the sample represents its share in the population. Used to correct samples that do not reflect the characteristics of the population. Also called poststratification weighting.

The loss of precision due to a particular complex survey sampling design.

A procedure for giving some individuals in the data more, or less, weight in the analysis. Often required when disproportionate or complex sampling is used.

A probability sampling method in which more aggregated units (clusters) are sampled before sampling individuals.

Complex Survey Sampling *This question is required

The comparable sample size from a simple random sample; it expresses the design effect (often a loss) due to complex sampling.

A probability sampling method in which more aggregated units (clusters) are sampled and then sampling occurs within the aggregates.

Adjustment of sample statistics to ensure that each stratum's share of the sample represents its share in the population. Used to correct samples that do not reflect the characteristics of the population. Also called poststratification adjustment.

Probability sampling methods that are more complex than simple random sampling, such as cluster sampling, stratified sampling, and disproportionate sampling.

Similarity of elements within a cluster. Also referred to as rho - the rate of homogeneity.

Adjustment of sample statistics to ensure that each stratum's share of the sample represents its share in the population. Used to correct samples that do not reflect the characteristics of the population. Also called poststratification weighting.

The loss of precision due to a particular complex survey sampling design.

A procedure for giving some individuals in the data more, or less, weight in the analysis. Often required when disproportionate or complex sampling is used.

A probability sampling method in which more aggregated units (clusters) are sampled before sampling individuals.

Design Effect *This question is required

The comparable sample size from a simple random sample; it expresses the design effect (often a loss) due to complex sampling.

A probability sampling method in which more aggregated units (clusters) are sampled and then sampling occurs within the aggregates.

Adjustment of sample statistics to ensure that each stratum's share of the sample represents its share in the population. Used to correct samples that do not reflect the characteristics of the population. Also called poststratification adjustment.

Probability sampling methods that are more complex than simple random sampling, such as cluster sampling, stratified sampling, and disproportionate sampling.

Similarity of elements within a cluster. Also referred to as rho - the rate of homogeneity.

Adjustment of sample statistics to ensure that each stratum's share of the sample represents its share in the population. Used to correct samples that do not reflect the characteristics of the population. Also called poststratification weighting.

The loss of precision due to a particular complex survey sampling design.

A procedure for giving some individuals in the data more, or less, weight in the analysis. Often required when disproportionate or complex sampling is used.

A probability sampling method in which more aggregated units (clusters) are sampled before sampling individuals.

7. When data are collected on the entire population, this type of study is referred to as *This question is required.

A sample

A census

A survey

A inference

8. The process of estimating characteristics of an entire group of units based on the characteristics of a subset of that group is called making *This question is required.

A sample

A census

A population

An inference

9. A doctor wanted to learn about the use of preventive health care services among low-income men. She conducted a survey in the waiting room of the clinic where she worked. This type of sample is called *This question is required.

Convenience sampling

Random sampling

Systematic sampling

Stratified sampling

10. A professor is studying relationships between siblings. Twins are a group of special interest. Which of the following would be a way to make sure enough twins are in the study to examine as a separate subgroup? *This question is required.

Oversampling

Stratified sampling

Cluster sampling

Systematic sampling

11. Which type of sampling is usually more clearly generalizable? *This question is required.

Convenience sample

Snowball sample

Random sample

Voluntary sample

12. A local health department conducted a survey by calling household telephones in order to ask questions related to HIV/AIDS prevention and related behaviors. The survey, however, did not call cell phones and thus missed many younger people. This problem is called: *This question is required.