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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

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

A subset of people or elements selected from a population.

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

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

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

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

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

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

The population the study aims to investigate.

A sample consisting of volunteers.

Random Sample

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

A subset of people or elements selected from a population.

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

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

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

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

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

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

The population the study aims to investigate.

A sample consisting of volunteers.

External Validity

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

A subset of people or elements selected from a population.

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

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

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

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

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

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

The population the study aims to investigate.

A sample consisting of volunteers.

Sampling

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

A subset of people or elements selected from a population.

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

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

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

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

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

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

The population the study aims to investigate.

A sample consisting of volunteers.

Sample *This question is required

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

A subset of people or elements selected from a population.

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

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

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

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

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

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

The population the study aims to investigate.

A sample consisting of volunteers.

Replication *This question is required

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

A subset of people or elements selected from a population.

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

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

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

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

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

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

The population the study aims to investigate.

A sample consisting of volunteers.

Convenience Sample

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

A subset of people or elements selected from a population.

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

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

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

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

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

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

The population the study aims to investigate.

A sample consisting of volunteers.

Population of Interest

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

A subset of people or elements selected from a population.

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

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

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

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

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

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

The population the study aims to investigate.

A sample consisting of volunteers.

Probability Sample

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

A subset of people or elements selected from a population.

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

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

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

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

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

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

The population the study aims to investigate.

A sample consisting of volunteers.

Meta-Analysis *This question is required

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

A subset of people or elements selected from a population.

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

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

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

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

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

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

The population the study aims to investigate.

A sample consisting of volunteers.

Voluntary Sample

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

A subset of people or elements selected from a population.

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

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

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

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

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

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

The population the study aims to investigate.

A sample consisting of volunteers.

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

Space Cell

Every member of a population. Contrasts with a sample.

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

The population the study aims to investigate.

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.

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

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.

Likelihood of responding to a survey or survey question.

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

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

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

Response Rate

Every member of a population. Contrasts with a sample.

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

The population the study aims to investigate.

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.

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

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.

Likelihood of responding to a survey or survey question.

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

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

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

Coverage Bias

Every member of a population. Contrasts with a sample.

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

The population the study aims to investigate.

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.

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

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.

Likelihood of responding to a survey or survey question.

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

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

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

Inference

Every member of a population. Contrasts with a sample.

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

The population the study aims to investigate.

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.

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

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.

Likelihood of responding to a survey or survey question.

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

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

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

Propensity to Respond *This question is required

Every member of a population. Contrasts with a sample.

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

The population the study aims to investigate.

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.

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

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.

Likelihood of responding to a survey or survey question.

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

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

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

Cooperation Rate *This question is required

Every member of a population. Contrasts with a sample.

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

The population the study aims to investigate.

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.

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

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.

Likelihood of responding to a survey or survey question.

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

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

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

Census

Every member of a population. Contrasts with a sample.

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

The population the study aims to investigate.

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.

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

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.

Likelihood of responding to a survey or survey question.

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

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

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

Random Digit Dialing (RDD)

Every member of a population. Contrasts with a sample.

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

The population the study aims to investigate.

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.

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

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.

Likelihood of responding to a survey or survey question.

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

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

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

Contact Rate *This question is required

Every member of a population. Contrasts with a sample.

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

The population the study aims to investigate.

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.

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

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.

Likelihood of responding to a survey or survey question.

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

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

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

Sampling Frame

Every member of a population. Contrasts with a sample.

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

The population the study aims to investigate.

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.

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

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.

Likelihood of responding to a survey or survey question.

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

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

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

Universe

Every member of a population. Contrasts with a sample.

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

The population the study aims to investigate.

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.

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

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.

Likelihood of responding to a survey or survey question.

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

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

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

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

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

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

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

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.

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.

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.

The distribution of statistics estimated from many repeated samples.

Respondent-Driven Sampling

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

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

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

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

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.

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.

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.

The distribution of statistics estimated from many repeated samples.

Snowball Sampling

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

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

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

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

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.

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.

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.

The distribution of statistics estimated from many repeated samples.

Sampling Distribution *This question is required

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

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

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

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

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.

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.

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.

The distribution of statistics estimated from many repeated samples.

Sampling Variability

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

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

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

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

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.

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.

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.

The distribution of statistics estimated from many repeated samples.

Nonresponse Bias

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

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

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

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

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.

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.

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.

The distribution of statistics estimated from many repeated samples.

Simple Random Sampling

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

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

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

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

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.

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.

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.

The distribution of statistics estimated from many repeated samples.

Random Sampling (or Probability Sampling)

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

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

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

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

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.

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.

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.

The distribution of statistics estimated from many repeated samples.

Sampling Error *This question is required

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

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

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

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

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.

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.

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.

The distribution of statistics estimated from many repeated samples.

Normal Distribution *This question is required

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

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

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

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

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.

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.

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.

The distribution of statistics estimated from many repeated samples.

Volunteer Bias

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

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

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

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

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.

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.

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.

The distribution of statistics estimated from many repeated samples.

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

Space Cell

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.

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

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

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.

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.

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

Standard Error

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.

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

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

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.

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.

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

Confidence Interval

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.

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

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

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.

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.

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

Margin of Error

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.

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

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

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.

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.

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

True Sample

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.

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

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

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.

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.

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

Observed Sample

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.

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

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

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.

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.

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

Systematic Sampling

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.

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

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

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.

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.

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

Strata

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.

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

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

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.

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.

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

Stratified Sampling *This question is required

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.

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

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

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.

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.

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

Oversampling *This question is required

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.

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

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

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.

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.

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

Disproportinate Sampling *This question is required

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.

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

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

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.

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.

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

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.

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.

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 adjustment.

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

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

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.

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.

Weighting

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

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 adjustment.

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

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

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.

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.

Effective Sample Size

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

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 adjustment.

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

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

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.

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.

Poststratification Adjustment

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

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 adjustment.

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

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

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.

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.

Poststratification Weighting

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

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 adjustment.

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

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

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.

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.

Multistage Sampling

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

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 adjustment.

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

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

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.

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.

Cluster Sampling

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

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 adjustment.

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

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

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.

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.

Intraclass Correlation

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

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 adjustment.

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

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

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.

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.

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.

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.

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 adjustment.

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

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

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.

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.

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.

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.

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 adjustment.

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

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

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.

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.

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.