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

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

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

Space Cell

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

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

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

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

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

A sample consisting of volunteers.

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

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

Random Sample

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

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

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

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

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

A sample consisting of volunteers.

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

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

Probability Sample

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

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

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

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

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

A sample consisting of volunteers.

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

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

Sampling

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

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

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

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

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

A sample consisting of volunteers.

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

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

Sample *This question is required

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

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

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

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

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

A sample consisting of volunteers.

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

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

Population of Interest

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

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

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

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

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

A sample consisting of volunteers.

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

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

Convenience Sample

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

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

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

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

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

A sample consisting of volunteers.

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

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

Voluntary Sample

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

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

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

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

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

A sample consisting of volunteers.

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

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

Meta-Analysis *This question is required

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

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

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

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

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

A sample consisting of volunteers.

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

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

Replication *This question is required

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

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

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

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

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

A sample consisting of volunteers.

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

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

External Validity

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

A subset of people or elements selected from a population.

The population the study aims to investigate.

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

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

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

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

A sample consisting of volunteers.

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

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

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

Space Cell

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

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.

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

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.

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

The population the study aims to investigate.

Every member of a population. Contrasts with a sample.

Census

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

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.

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

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.

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

The population the study aims to investigate.

Every member of a population. Contrasts with a sample.

Contact Rate *This question is required

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

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.

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

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.

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

The population the study aims to investigate.

Every member of a population. Contrasts with a sample.

Response Rate

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

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.

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

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.

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

The population the study aims to investigate.

Every member of a population. Contrasts with a sample.

Universe

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

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.

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

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.

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

The population the study aims to investigate.

Every member of a population. Contrasts with a sample.

Cooperation Rate *This question is required

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

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.

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

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.

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

The population the study aims to investigate.

Every member of a population. Contrasts with a sample.

Coverage Bias

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

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.

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

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.

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

The population the study aims to investigate.

Every member of a population. Contrasts with a sample.

Inference

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

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.

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

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.

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

The population the study aims to investigate.

Every member of a population. Contrasts with a sample.

Random Digit Dialing (RDD)

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

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.

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

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.

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

The population the study aims to investigate.

Every member of a population. Contrasts with a sample.

Sampling Frame

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

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.

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

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.

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

The population the study aims to investigate.

Every member of a population. Contrasts with a sample.

Propensity to Respond *This question is required

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

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.

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

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.

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

The population the study aims to investigate.

Every member of a population. Contrasts with a sample.

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

Space Cell

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

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

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

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

Bias in 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.

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

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

The distribution of statistics estimated from many repeated samples.

Choosing from the sampling frame at random.

Sampling Distribution *This question is required

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

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

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

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

Bias in 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.

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

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

The distribution of statistics estimated from many repeated samples.

Choosing from the sampling frame at random.

Normal Distribution *This question is required

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

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

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

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

Bias in 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.

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

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

The distribution of statistics estimated from many repeated samples.

Choosing from the sampling frame at random.

Volunteer Bias

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

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

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

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

Bias in 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.

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

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

The distribution of statistics estimated from many repeated samples.

Choosing from the sampling frame at random.

Snowball Sampling

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

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

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

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

Bias in 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.

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

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

The distribution of statistics estimated from many repeated samples.

Choosing from the sampling frame at random.

Respondent-Driven Sampling

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

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

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

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

Bias in 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.

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

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

The distribution of statistics estimated from many repeated samples.

Choosing from the sampling frame at random.

Random Sampling (or Probability Sampling)

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

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

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

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

Bias in 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.

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

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

The distribution of statistics estimated from many repeated samples.

Choosing from the sampling frame at random.

Sampling Variability

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

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

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

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

Bias in 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.

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

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

The distribution of statistics estimated from many repeated samples.

Choosing from the sampling frame at random.

Simple Random Sampling

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

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

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

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

Bias in 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.

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

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

The distribution of statistics estimated from many repeated samples.

Choosing from the sampling frame at random.

Nonresponse Bias

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

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

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

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

Bias in 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.

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

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

The distribution of statistics estimated from many repeated samples.

Choosing from the sampling frame at random.

Sampling Error *This question is required

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

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

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

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

Bias in 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.

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

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

The distribution of statistics estimated from many repeated samples.

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.

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

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

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

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

A 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.

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

Standard Error

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

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

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

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

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

A 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.

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

Confidence Interval

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

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

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

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

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

A 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.

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

Margin of Error

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

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

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

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

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

A 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.

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

True Sample

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

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

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

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

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

A 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.

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

Observed Sample

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

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

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

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

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

A 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.

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

Systematic Sampling

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

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

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

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

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

A 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.

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

Strata

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

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

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

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

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

A 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.

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

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.

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

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

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

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

A 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.

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

Oversampling *This question is required

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

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

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

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

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

A 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.

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

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.

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

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

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

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

A 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.

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

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

Space Cell

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

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

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 and then sampling occurs within the aggregates.

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

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.

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.

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

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

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

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

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.

Effective Sample Size

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

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

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 and then sampling occurs within the aggregates.

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

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.

Poststratification Adjustment

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

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

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 and then sampling occurs within the aggregates.

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

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.

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.

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

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

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

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

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.

Multistage Sampling

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

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

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 and then sampling occurs within the aggregates.

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

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.

Cluster Sampling

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

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

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 and then sampling occurs within the aggregates.

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

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.

Intraclass Correlation

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

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

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 and then sampling occurs within the aggregates.

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

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.

Complex Survey Sampling *This question is required

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

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

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 and then sampling occurs within the aggregates.

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

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.

Design Effect *This question is required

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

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

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 and then sampling occurs within the aggregates.

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

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.

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.