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

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

The population the study aims to investigate.

A sample consisting of volunteers.

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

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

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

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

A subset of people or elements selected from a population.

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

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

The population the study aims to investigate.

A sample consisting of volunteers.

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

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

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

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

A subset of people or elements selected from a population.

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

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

The population the study aims to investigate.

A sample consisting of volunteers.

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

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

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

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

A subset of people or elements selected from a population.

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

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

The population the study aims to investigate.

A sample consisting of volunteers.

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

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

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

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

A subset of people or elements selected from a population.

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

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

The population the study aims to investigate.

A sample consisting of volunteers.

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

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

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

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

A subset of people or elements selected from a population.

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

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

The population the study aims to investigate.

A sample consisting of volunteers.

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

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

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

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

A subset of people or elements selected from a population.

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

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

The population the study aims to investigate.

A sample consisting of volunteers.

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

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

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

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

A subset of people or elements selected from a population.

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

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

The population the study aims to investigate.

A sample consisting of volunteers.

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

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

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

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

A subset of people or elements selected from a population.

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

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

The population the study aims to investigate.

A sample consisting of volunteers.

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

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

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

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

A subset of people or elements selected from a population.

Sampling

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

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

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

The population the study aims to investigate.

A sample consisting of volunteers.

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

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

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

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

A subset of people or elements selected from a population.

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

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

The population the study aims to investigate.

A sample consisting of volunteers.

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

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

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

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

A subset of people or elements selected from a population.

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

Space Cell

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

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

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

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

Likelihood of responding to a survey or survey question.

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

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

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.

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

Contact Rate *This question is required

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

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

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

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

Likelihood of responding to a survey or survey question.

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

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

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.

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

Response Rate

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

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

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

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

Likelihood of responding to a survey or survey question.

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

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

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.

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

Propensity to Respond *This question is required

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

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

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

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

Likelihood of responding to a survey or survey question.

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

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

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.

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

Coverage Bias

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

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

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

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

Likelihood of responding to a survey or survey question.

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

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

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.

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

Cooperation Rate *This question is required

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

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

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

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

Likelihood of responding to a survey or survey question.

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

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

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.

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

Census

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

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

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

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

Likelihood of responding to a survey or survey question.

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

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

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.

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

Random Digit Dialing (RDD)

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

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

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

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

Likelihood of responding to a survey or survey question.

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

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

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.

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

Inference

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

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

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

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

Likelihood of responding to a survey or survey question.

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

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

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.

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

Sampling Frame

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

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

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

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

Likelihood of responding to a survey or survey question.

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

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

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.

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

Universe

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

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

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

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

Likelihood of responding to a survey or survey question.

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

Every member of a population. Contrasts with a sample.

The population the study aims to investigate.

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.

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

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

Space Cell

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

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

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

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

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.

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.

The distribution of statistics estimated from many repeated samples.

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

Choosing from the sampling frame at random.

Snowball Sampling

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

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.

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

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

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.

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.

The distribution of statistics estimated from many repeated samples.

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

Choosing from the sampling frame at random.

Simple Random Sampling

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

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.

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

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

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.

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.

The distribution of statistics estimated from many repeated samples.

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

Choosing from the sampling frame at random.

Volunteer Bias

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

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.

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

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

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.

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.

The distribution of statistics estimated from many repeated samples.

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

Choosing from the sampling frame at random.

Sampling Distribution *This question is required

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

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

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

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

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.

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.

The distribution of statistics estimated from many repeated samples.

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

Choosing from the sampling frame at random.

Sampling Error *This question is required

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

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

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

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

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.

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.

The distribution of statistics estimated from many repeated samples.

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

Choosing from the sampling frame at random.

Random Sampling (or Probability Sampling)

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

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

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

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

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.

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.

The distribution of statistics estimated from many repeated samples.

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

Choosing from the sampling frame at random.

Sampling Variability

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

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.

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

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

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.

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.

The distribution of statistics estimated from many repeated samples.

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

Choosing from the sampling frame at random.

Normal Distribution *This question is required

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

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

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

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

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.

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.

The distribution of statistics estimated from many repeated samples.

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

Choosing from the sampling frame at random.

Respondent-Driven Sampling

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

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.

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

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

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.

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.

The distribution of statistics estimated from many repeated samples.

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

Choosing from the sampling frame at random.

Nonresponse Bias

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

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.

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

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

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.

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.

The distribution of statistics estimated from many repeated samples.

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

Choosing from the sampling frame at random.

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

Space Cell

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

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

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

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

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.

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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.

Standard Error

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

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

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

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

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.

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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.

Confidence Interval

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

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

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

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

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.

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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.

Margin of Error

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

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

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

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

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.

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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.

True Sample

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

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

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

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

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.

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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.

Observed Sample

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

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

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

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

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.

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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.

Systematic Sampling

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

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

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

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

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.

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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.

Strata

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

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

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

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

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.

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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.

Stratified Sampling *This question is required

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

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

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

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

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.

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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.

Oversampling *This question is required

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

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

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

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

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.

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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.

Disproportinate Sampling *This question is required

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

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

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

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

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.

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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.

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

Space Cell

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

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

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

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.

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

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

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

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

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

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

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

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.

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

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

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

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

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

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

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

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.

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

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

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

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

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

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

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

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.

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

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

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

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

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

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

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

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.

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

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

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

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

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

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

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

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.

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

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

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

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

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

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

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

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.

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

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

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

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

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

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

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

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.

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

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

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

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

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

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

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

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.

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

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

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

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

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

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

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

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.

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

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

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

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.