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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.

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.

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

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

Convenience Sample

The population the study aims to investigate.

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.

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

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

Meta-Analysis *This question is required

The population the study aims to investigate.

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.

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

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

Sampling

The population the study aims to investigate.

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.

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

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

Replication *This question is required

The population the study aims to investigate.

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.

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

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

Random Sample

The population the study aims to investigate.

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.

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

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

Population of Interest

The population the study aims to investigate.

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.

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

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

Sample *This question is required

The population the study aims to investigate.

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.

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

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

External Validity

The population the study aims to investigate.

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.

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

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

Probability Sample

The population the study aims to investigate.

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.

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

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

Voluntary Sample

The population the study aims to investigate.

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.

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

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

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

A subset of people or elements selected from a population.

A sample consisting of volunteers.

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

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

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

Space Cell

Every member of a population. Contrasts with a sample.

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

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.

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

The population the study aims to investigate.

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

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

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

Likelihood of responding to a survey or survey question.

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

Coverage Bias

Every member of a population. Contrasts with a sample.

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

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.

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

The population the study aims to investigate.

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

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

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

Likelihood of responding to a survey or survey question.

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

Universe

Every member of a population. Contrasts with a sample.

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

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.

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

The population the study aims to investigate.

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

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

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

Likelihood of responding to a survey or survey question.

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

Inference

Every member of a population. Contrasts with a sample.

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

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.

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

The population the study aims to investigate.

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

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

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

Likelihood of responding to a survey or survey question.

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

Contact Rate *This question is required

Every member of a population. Contrasts with a sample.

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

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.

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

The population the study aims to investigate.

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

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

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

Likelihood of responding to a survey or survey question.

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

Response Rate

Every member of a population. Contrasts with a sample.

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

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.

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

The population the study aims to investigate.

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

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

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

Likelihood of responding to a survey or survey question.

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

Sampling Frame

Every member of a population. Contrasts with a sample.

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

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.

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

The population the study aims to investigate.

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

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

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

Likelihood of responding to a survey or survey question.

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

Cooperation Rate *This question is required

Every member of a population. Contrasts with a sample.

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

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.

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

The population the study aims to investigate.

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

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

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

Likelihood of responding to a survey or survey question.

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

Propensity to Respond *This question is required

Every member of a population. Contrasts with a sample.

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

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.

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

The population the study aims to investigate.

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

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

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

Likelihood of responding to a survey or survey question.

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

Census

Every member of a population. Contrasts with a sample.

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

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.

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

The population the study aims to investigate.

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

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

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

Likelihood of responding to a survey or survey question.

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

Random Digit Dialing (RDD)

Every member of a population. Contrasts with a sample.

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

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.

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

The population the study aims to investigate.

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

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

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

Likelihood of responding to a survey or survey question.

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

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

Space Cell

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

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

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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

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

Random Sampling (or Probability Sampling)

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

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

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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

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

Volunteer Bias

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

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

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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

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

Sampling Error *This question is required

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

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

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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

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

Nonresponse Bias

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

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

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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

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

Snowball Sampling

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

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

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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

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

Simple Random Sampling

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

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

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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

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

Respondent-Driven Sampling

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

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

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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

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

Sampling Distribution *This question is required

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

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

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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

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

Normal Distribution *This question is required

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

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

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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

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

Sampling Variability

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

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

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

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

Choosing from the sampling frame at random.

The distribution of statistics estimated from many repeated samples.

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

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

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

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

Space Cell

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

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

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

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.

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 individuals or elements are sampled at even intervals - every kth individual for some integer k.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

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

Standard Error

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

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

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

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.

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 individuals or elements are sampled at even intervals - every kth individual for some integer k.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

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

Confidence Interval

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

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

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

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.

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 individuals or elements are sampled at even intervals - every kth individual for some integer k.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

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

Margin of Error

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

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

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

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.

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 individuals or elements are sampled at even intervals - every kth individual for some integer k.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

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

True Sample

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

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

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

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.

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 individuals or elements are sampled at even intervals - every kth individual for some integer k.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

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

Observed Sample

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

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

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

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.

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 individuals or elements are sampled at even intervals - every kth individual for some integer k.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

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

Systematic Sampling

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

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

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

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.

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 individuals or elements are sampled at even intervals - every kth individual for some integer k.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

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

Strata

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

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

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

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.

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 individuals or elements are sampled at even intervals - every kth individual for some integer k.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

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

Stratified Sampling *This question is required

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

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

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

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.

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 individuals or elements are sampled at even intervals - every kth individual for some integer k.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

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

Oversampling *This question is required

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

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

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

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.

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 individuals or elements are sampled at even intervals - every kth individual for some integer k.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

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

Disproportinate Sampling *This question is required

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

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

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

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.

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 individuals or elements are sampled at even intervals - every kth individual for some integer k.

A range of values in which we have a defined level of confidence (e.g. 95%) that the true value of the statistic being estimated lies.

The 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

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

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

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

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

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

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

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

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

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

Weighting

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

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

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

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

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

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

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

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

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

Effective Sample Size

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

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

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

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

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

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

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

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

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

Poststratification Adjustment

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

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

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

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

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

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

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

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

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

Poststratification Weighting

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

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

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

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

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

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

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

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

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

Multistage Sampling

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

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

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

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

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

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

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

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

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

Cluster Sampling

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

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

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

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

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

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

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

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

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

Intraclass Correlation

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

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

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

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

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

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

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

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

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

Complex Survey Sampling *This question is required

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

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

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

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

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

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

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

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

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

Design Effect *This question is required

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

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

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

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

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

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

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

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

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

7. When data are collected on the entire population, this type of study is referred to as *This question is required.

A sample

A census

A survey

A inference

8. The process of estimating characteristics of an entire group of units based on the characteristics of a subset of that group is called making *This question is required.

A sample

A census

A population

An inference

9. A doctor wanted to learn about the use of preventive health care services among low-income men. She conducted a survey in the waiting room of the clinic where she worked. This type of sample is called *This question is required.

Convenience sampling

Random sampling

Systematic sampling

Stratified sampling

10. A professor is studying relationships between siblings. Twins are a group of special interest. Which of the following would be a way to make sure enough twins are in the study to examine as a separate subgroup? *This question is required.

Oversampling

Stratified sampling

Cluster sampling

Systematic sampling

11. Which type of sampling is usually more clearly generalizable? *This question is required.

Convenience sample

Snowball sample

Random sample

Voluntary sample

12. A local health department conducted a survey by calling household telephones in order to ask questions related to HIV/AIDS prevention and related behaviors. The survey, however, did not call cell phones and thus missed many younger people. This problem is called: *This question is required.