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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

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

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

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

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.

A sample consisting of volunteers.

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

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

Population of Interest

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

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

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

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.

A sample consisting of volunteers.

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

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

Meta-Analysis *This question is required

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

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

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

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.

A sample consisting of volunteers.

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

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

Random Sample

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

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

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

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.

A sample consisting of volunteers.

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

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

Voluntary Sample

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

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

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

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.

A sample consisting of volunteers.

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

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

Sample *This question is required

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

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

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

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.

A sample consisting of volunteers.

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

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

Sampling

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

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

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

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.

A sample consisting of volunteers.

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

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

External Validity

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

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

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

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.

A sample consisting of volunteers.

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

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

Replication *This question is required

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

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

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

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.

A sample consisting of volunteers.

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

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

Probability Sample

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

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

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

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.

A sample consisting of volunteers.

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

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

Convenience Sample

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

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

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

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.

A sample consisting of volunteers.

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

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

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.

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.

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

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

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

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

Likelihood of responding to a survey or survey question.

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.

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.

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

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

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

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

Likelihood of responding to a survey or survey question.

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.

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.

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

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

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

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

Likelihood of responding to a survey or survey question.

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.

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.

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

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

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

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

Likelihood of responding to a survey or survey question.

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.

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.

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

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

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

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

Likelihood of responding to a survey or survey question.

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.

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.

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

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

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

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

Likelihood of responding to a survey or survey question.

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.

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.

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

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

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

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

Likelihood of responding to a survey or survey question.

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.

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.

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

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

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

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

Likelihood of responding to a survey or survey question.

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.

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.

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

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

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

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

Likelihood of responding to a survey or survey question.

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.

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.

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

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

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

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

Likelihood of responding to a survey or survey question.

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.

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.

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

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

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

The population the study aims to investigate.

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

Every member of a population. Contrasts with a sample.

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

Likelihood of responding to a survey or survey question.

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

Space Cell

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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.

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

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

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

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

Simple Random Sampling

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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.

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

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

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

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

Sampling Distribution *This question is required

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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.

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

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

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

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

Sampling Error *This question is required

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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.

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

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

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

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

Sampling Variability

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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.

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

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

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

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

Snowball Sampling

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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.

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

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

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

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

Nonresponse Bias

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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.

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

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

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

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

Respondent-Driven Sampling

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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.

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

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

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

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

Volunteer Bias

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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.

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

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

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

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

Random Sampling (or Probability Sampling)

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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.

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

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

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

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

Normal Distribution *This question is required

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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.

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

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

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

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

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

Space Cell

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

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

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.

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.

Standard Error

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

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

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.

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.

Confidence Interval

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

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

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.

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.

Margin of Error

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

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

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.

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.

True Sample

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

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

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.

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.

Observed Sample

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

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

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.

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.

Systematic Sampling

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

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

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.

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.

Strata

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

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

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.

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.

Stratified Sampling *This question is required

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

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

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.

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.

Oversampling *This question is required

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

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

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.

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.

Disproportinate Sampling *This question is required

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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.

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

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

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

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.

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.

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

Space Cell

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.

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

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

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

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

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.

Weighting

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.

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

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

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

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

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.

Effective Sample Size

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.

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

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

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

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

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.

Poststratification Adjustment

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.

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

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

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

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

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.

Poststratification Weighting

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.

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

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

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

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

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.

Multistage Sampling

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.

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

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

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

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

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.

Cluster Sampling

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.

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

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

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

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

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.

Intraclass Correlation

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.

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

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

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

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

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.

Complex Survey Sampling *This question is required

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.

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

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

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

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

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.

Design Effect *This question is required

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.

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

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

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

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

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.

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.