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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

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

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

The population the study aims to investigate.

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

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

Population of Interest

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

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

The population the study aims to investigate.

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

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

Convenience Sample

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

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

The population the study aims to investigate.

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

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

Sample *This question is required

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

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

The population the study aims to investigate.

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

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

Replication *This question is required

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

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

The population the study aims to investigate.

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

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

Voluntary Sample

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

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

The population the study aims to investigate.

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

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

Meta-Analysis *This question is required

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

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

The population the study aims to investigate.

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

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

Sampling

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

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

The population the study aims to investigate.

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

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

Probability Sample

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

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

The population the study aims to investigate.

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

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

External Validity

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

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

The population the study aims to investigate.

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

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

Random Sample

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

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

The population the study aims to investigate.

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

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

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

Space Cell

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.

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

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

Likelihood of responding to a survey or survey question.

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 cooperate with a survey request from among those contacted.

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

Contact Rate *This question is required

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.

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

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

Likelihood of responding to a survey or survey question.

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 cooperate with a survey request from among those contacted.

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

Cooperation Rate *This question is required

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.

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

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

Likelihood of responding to a survey or survey question.

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 cooperate with a survey request from among those contacted.

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

Propensity to Respond *This question is required

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.

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

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

Likelihood of responding to a survey or survey question.

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 cooperate with a survey request from among those contacted.

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

Response Rate

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.

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

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

Likelihood of responding to a survey or survey question.

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 cooperate with a survey request from among those contacted.

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

Random Digit Dialing (RDD)

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.

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

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

Likelihood of responding to a survey or survey question.

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 cooperate with a survey request from among those contacted.

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

Sampling Frame

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.

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

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

Likelihood of responding to a survey or survey question.

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 cooperate with a survey request from among those contacted.

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

Census

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.

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

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

Likelihood of responding to a survey or survey question.

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 cooperate with a survey request from among those contacted.

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

Universe

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.

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

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

Likelihood of responding to a survey or survey question.

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 cooperate with a survey request from among those contacted.

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

Coverage Bias

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.

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

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

Likelihood of responding to a survey or survey question.

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 cooperate with a survey request from among those contacted.

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

Inference

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.

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

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

Likelihood of responding to a survey or survey question.

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 cooperate with a survey request from among those contacted.

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

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

Space Cell

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.

Choosing from the sampling frame at random.

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

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

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.

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

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

The distribution of statistics estimated from many repeated samples.

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.

Volunteer Bias

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.

Choosing from the sampling frame at random.

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

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

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.

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

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

The distribution of statistics estimated from many repeated samples.

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.

Simple Random Sampling

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.

Choosing from the sampling frame at random.

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

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

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.

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

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

The distribution of statistics estimated from many repeated samples.

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.

Nonresponse Bias

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.

Choosing from the sampling frame at random.

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

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

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.

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

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

The distribution of statistics estimated from many repeated samples.

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.

Sampling Error *This question is required

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.

Choosing from the sampling frame at random.

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

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

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.

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

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

The distribution of statistics estimated from many repeated samples.

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.

Sampling Variability

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.

Choosing from the sampling frame at random.

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

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

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.

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

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

The distribution of statistics estimated from many repeated samples.

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.

Respondent-Driven Sampling

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.

Choosing from the sampling frame at random.

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

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

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.

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

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

The distribution of statistics estimated from many repeated samples.

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.

Normal Distribution *This question is required

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.

Choosing from the sampling frame at random.

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

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

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.

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

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

The distribution of statistics estimated from many repeated samples.

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.

Snowball Sampling

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.

Choosing from the sampling frame at random.

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

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

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.

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

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

The distribution of statistics estimated from many repeated samples.

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.

Random Sampling (or Probability Sampling)

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.

Choosing from the sampling frame at random.

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

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

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.

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

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

The distribution of statistics estimated from many repeated samples.

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.

Sampling Distribution *This question is required

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.

Choosing from the sampling frame at random.

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

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

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.

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

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

The distribution of statistics estimated from many repeated samples.

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.

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

Space Cell

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.

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

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

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

Standard Error

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.

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

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

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

Confidence Interval

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.

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

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

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

Margin of Error

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.

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

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

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

True Sample

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.

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

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

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

Observed Sample

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.

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

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

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

Systematic Sampling

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.

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

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

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

Strata

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.

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

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

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

Stratified Sampling *This question is required

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.

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

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

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

Oversampling *This question is required

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.

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

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

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

Disproportinate Sampling *This question is required

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.

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

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

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

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

Space Cell

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.

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.

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.

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

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

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

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.

Weighting

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.

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.

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.

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

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

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

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.

Effective Sample Size

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.

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.

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.

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

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

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

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.

Poststratification Adjustment

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.

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.

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.

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

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

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

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.

Poststratification Weighting

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.

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.

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.

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

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

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

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.

Multistage Sampling

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.

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.

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.

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

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

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

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.

Cluster Sampling

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.

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.

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.

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

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

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

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.

Intraclass Correlation

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.

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.

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.

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

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

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

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.

Complex Survey Sampling *This question is required

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.

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.

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.

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

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

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

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.

Design Effect *This question is required

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.

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.

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.

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

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

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

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.

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.