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

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

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

Space Cell

The population the study aims to investigate.

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

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

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

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

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.

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

Convenience Sample

The population the study aims to investigate.

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

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

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

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

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.

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

Replication *This question is required

The population the study aims to investigate.

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

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

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

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

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.

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

Meta-Analysis *This question is required

The population the study aims to investigate.

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

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

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

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

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.

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

Random Sample

The population the study aims to investigate.

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

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

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

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

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.

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

Sampling

The population the study aims to investigate.

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

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

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

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

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.

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

Probability Sample

The population the study aims to investigate.

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

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

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

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

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.

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

Voluntary Sample

The population the study aims to investigate.

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

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

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

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

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.

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

Population of Interest

The population the study aims to investigate.

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

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

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

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

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.

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

External Validity

The population the study aims to investigate.

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

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

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

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

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.

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

Sample *This question is required

The population the study aims to investigate.

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

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

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

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

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.

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

Space Cell

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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

Every member of a population. Contrasts with a sample.

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

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

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

Propensity to Respond *This question is required

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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

Every member of a population. Contrasts with a sample.

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

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

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

Cooperation Rate *This question is required

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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

Every member of a population. Contrasts with a sample.

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

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

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

Inference

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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

Every member of a population. Contrasts with a sample.

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

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

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

Census

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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

Every member of a population. Contrasts with a sample.

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

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

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

Contact Rate *This question is required

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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

Every member of a population. Contrasts with a sample.

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

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

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

Response Rate

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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

Every member of a population. Contrasts with a sample.

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

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

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

Sampling Frame

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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

Every member of a population. Contrasts with a sample.

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

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

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

Universe

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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

Every member of a population. Contrasts with a sample.

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

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

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

Random Digit Dialing (RDD)

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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

Every member of a population. Contrasts with a sample.

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

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

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

Coverage Bias

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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

Every member of a population. Contrasts with a sample.

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

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

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

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.

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

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

The distribution of statistics estimated from many repeated samples.

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

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.

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

Choosing from the sampling frame at random.

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

Sampling Variability

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.

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

The distribution of statistics estimated from many repeated samples.

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

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.

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

Choosing from the sampling frame at random.

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

Snowball Sampling

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.

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

The distribution of statistics estimated from many repeated samples.

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

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.

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

Choosing from the sampling frame at random.

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

Simple Random Sampling

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.

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

The distribution of statistics estimated from many repeated samples.

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

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.

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

Choosing from the sampling frame at random.

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

Nonresponse Bias

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.

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

The distribution of statistics estimated from many repeated samples.

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

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.

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

Choosing from the sampling frame at random.

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

Respondent-Driven Sampling

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.

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

The distribution of statistics estimated from many repeated samples.

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

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.

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

Choosing from the sampling frame at random.

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

Sampling Error *This question is required

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.

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

The distribution of statistics estimated from many repeated samples.

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

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.

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

Choosing from the sampling frame at random.

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

Volunteer Bias

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.

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

The distribution of statistics estimated from many repeated samples.

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

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.

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

Choosing from the sampling frame at random.

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

Normal Distribution *This question is required

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.

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

The distribution of statistics estimated from many repeated samples.

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

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.

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

Choosing from the sampling frame at random.

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

Random Sampling (or Probability Sampling)

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.

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

The distribution of statistics estimated from many repeated samples.

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

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.

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

Choosing from the sampling frame at random.

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

Sampling Distribution *This question is required

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.

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

The distribution of statistics estimated from many repeated samples.

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

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.

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

Choosing from the sampling frame at random.

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

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

Space Cell

The amount added to the point estimate in both directions to create the 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 range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which 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 with probability greater than their population share. Also called disproportionate sampling.

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

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

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

Standard Error

The amount added to the point estimate in both directions to create the 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 range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which 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 with probability greater than their population share. Also called disproportionate sampling.

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

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

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

Confidence Interval

The amount added to the point estimate in both directions to create the 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 range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which 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 with probability greater than their population share. Also called disproportionate sampling.

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

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

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

Margin of Error

The amount added to the point estimate in both directions to create the 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 range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which 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 with probability greater than their population share. Also called disproportionate sampling.

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

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

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

True Sample

The amount added to the point estimate in both directions to create the 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 range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which 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 with probability greater than their population share. Also called disproportionate sampling.

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

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

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

Observed Sample

The amount added to the point estimate in both directions to create the 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 range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which 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 with probability greater than their population share. Also called disproportionate sampling.

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

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

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

Systematic Sampling

The amount added to the point estimate in both directions to create the 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 range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which 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 with probability greater than their population share. Also called disproportionate sampling.

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

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

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

Strata

The amount added to the point estimate in both directions to create the 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 range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which 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 with probability greater than their population share. Also called disproportionate sampling.

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

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

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

Stratified Sampling *This question is required

The amount added to the point estimate in both directions to create the 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 range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which 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 with probability greater than their population share. Also called disproportionate sampling.

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

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

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

Oversampling *This question is required

The amount added to the point estimate in both directions to create the 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 range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which 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 with probability greater than their population share. Also called disproportionate sampling.

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

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

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

Disproportinate Sampling *This question is required

The amount added to the point estimate in both directions to create the 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 range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

Probability sampling method in which 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 with probability greater than their population share. Also called disproportionate sampling.

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

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

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

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

Space Cell

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.

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

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

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

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

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

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

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

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

Weighting

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

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

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

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

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

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

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

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

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

Effective Sample Size

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

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

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

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

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

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

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

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

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

Poststratification Adjustment

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

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

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

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

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

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

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

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

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

Poststratification Weighting

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

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

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

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

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

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

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

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

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

Multistage Sampling

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

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

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

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

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

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

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

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

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

Cluster Sampling

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

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

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

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

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

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

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

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

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

Intraclass Correlation

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

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

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

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

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

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

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

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

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

Complex Survey Sampling *This question is required

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

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

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

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

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

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

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

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

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

Design Effect *This question is required

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

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

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

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

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

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

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

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

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

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.