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

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

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

Space Cell

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

The population the study aims to investigate.

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

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

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

A subset of people or elements selected from a population.

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

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

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

A sample consisting of volunteers.

Probability Sample

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

The population the study aims to investigate.

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

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

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

A subset of people or elements selected from a population.

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

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

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

A sample consisting of volunteers.

Sampling

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

The population the study aims to investigate.

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

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

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

A subset of people or elements selected from a population.

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

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

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

A sample consisting of volunteers.

Convenience Sample

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

The population the study aims to investigate.

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

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

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

A subset of people or elements selected from a population.

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

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

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

A sample consisting of volunteers.

Population of Interest

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

The population the study aims to investigate.

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

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

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

A subset of people or elements selected from a population.

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

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

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

A sample consisting of volunteers.

Sample *This question is required

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

The population the study aims to investigate.

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

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

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

A subset of people or elements selected from a population.

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

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

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

A sample consisting of volunteers.

Meta-Analysis *This question is required

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

The population the study aims to investigate.

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

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

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

A subset of people or elements selected from a population.

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

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

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

A sample consisting of volunteers.

Random Sample

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

The population the study aims to investigate.

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

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

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

A subset of people or elements selected from a population.

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

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

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

A sample consisting of volunteers.

Replication *This question is required

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

The population the study aims to investigate.

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

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

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

A subset of people or elements selected from a population.

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

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

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

A sample consisting of volunteers.

Voluntary Sample

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

The population the study aims to investigate.

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

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

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

A subset of people or elements selected from a population.

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

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

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

A sample consisting of volunteers.

External Validity

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

The population the study aims to investigate.

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

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

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

A subset of people or elements selected from a population.

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

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

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

A sample consisting of volunteers.

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

Space Cell

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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.

Every member of a population. Contrasts with a sample.

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

Propensity to Respond *This question is required

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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.

Every member of a population. Contrasts with a sample.

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

Response Rate

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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.

Every member of a population. Contrasts with a sample.

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

Contact Rate *This question is required

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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.

Every member of a population. Contrasts with a sample.

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

Census

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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.

Every member of a population. Contrasts with a sample.

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

Sampling Frame

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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.

Every member of a population. Contrasts with a sample.

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

Random Digit Dialing (RDD)

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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.

Every member of a population. Contrasts with a sample.

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

Universe

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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.

Every member of a population. Contrasts with a sample.

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

Inference

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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.

Every member of a population. Contrasts with a sample.

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

Coverage Bias

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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.

Every member of a population. Contrasts with a sample.

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

Cooperation Rate *This question is required

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

The population the study aims to investigate.

Likelihood of responding to a survey or survey question.

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

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.

Every member of a population. Contrasts with a sample.

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

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

Space Cell

Choosing from the sampling frame at random.

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.

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

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

The distribution of statistics estimated from many repeated samples.

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

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

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

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.

Sampling Distribution *This question is required

Choosing from the sampling frame at random.

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.

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

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

The distribution of statistics estimated from many repeated samples.

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

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

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

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.

Volunteer Bias

Choosing from the sampling frame at random.

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.

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

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

The distribution of statistics estimated from many repeated samples.

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

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

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

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.

Sampling Variability

Choosing from the sampling frame at random.

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.

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

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

The distribution of statistics estimated from many repeated samples.

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

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

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

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.

Normal Distribution *This question is required

Choosing from the sampling frame at random.

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.

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

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

The distribution of statistics estimated from many repeated samples.

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

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

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

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.

Simple Random Sampling

Choosing from the sampling frame at random.

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.

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

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

The distribution of statistics estimated from many repeated samples.

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

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

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

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.

Nonresponse Bias

Choosing from the sampling frame at random.

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.

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

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

The distribution of statistics estimated from many repeated samples.

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

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

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

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.

Snowball Sampling

Choosing from the sampling frame at random.

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.

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

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

The distribution of statistics estimated from many repeated samples.

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

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

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

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.

Random Sampling (or Probability Sampling)

Choosing from the sampling frame at random.

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.

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

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

The distribution of statistics estimated from many repeated samples.

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

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

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

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.

Respondent-Driven Sampling

Choosing from the sampling frame at random.

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.

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

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

The distribution of statistics estimated from many repeated samples.

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

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

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

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.

Sampling Error *This question is required

Choosing from the sampling frame at random.

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.

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

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

The distribution of statistics estimated from many repeated samples.

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

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

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

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.

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

Space Cell

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.

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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

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

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

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

Standard Error

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.

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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

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

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

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

Confidence Interval

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.

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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

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

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

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

Margin of Error

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.

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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

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

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

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

True Sample

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.

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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

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

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

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

Observed Sample

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.

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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

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

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

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

Systematic Sampling

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.

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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

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

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

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

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.

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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

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

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

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

Stratified Sampling *This question is required

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.

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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

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

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

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

Oversampling *This question is required

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.

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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

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

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

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

Disproportinate Sampling *This question is required

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.

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

Exhaustive and mutually exclusive subgroups of a target population.

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

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

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

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

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

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

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

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

Space Cell

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

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

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

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

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

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.

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

Weighting

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

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

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

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

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

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.

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

Effective Sample Size

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

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

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

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

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

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.

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

Poststratification Adjustment

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

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

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

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

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

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.

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

Poststratification Weighting

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

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

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

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

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

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.

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

Multistage Sampling

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

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

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

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

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

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.

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

Cluster Sampling

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

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

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

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

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

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.

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

Intraclass Correlation

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

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

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

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

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

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.

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

Complex Survey Sampling *This question is required

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

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

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

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

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

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.

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

Design Effect *This question is required

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

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

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

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

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

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.

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

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.