chapter7-PSYch

What is a population?

The entire set of people or things researchers are interested in studying.

What is a sample?

A smaller group selected from a population that researchers actually study.

What is the difference between a population and a sample?

The population is the entire group of interest, while the sample is the smaller group studied.

What is a census?

Studying every member of a population.

Why do psychologists study samples instead of entire populations?

Studying entire populations is often impractical, expensive, and time-consuming.

What is the purpose of studying samples?

To draw conclusions and make predictions about a larger population.

What is the population of interest?

The specific group to which researchers want their findings to generalize.

What is an example of a population and sample in voting research?

Population: all eligible voters. Sample: 1,000 voters surveyed about whom they plan to vote for.

What does it mean to generalize findings?

To apply results from a sample to the larger population of interest.

Why must a sample represent the population?

So researchers can make accurate inferences about the population.

What is a representative sample?

A sample that reflects the characteristics and proportions of the population.

What is an unrepresentative sample?

A sample that does not accurately reflect the population.

What is a biased sample?

A sample in which members of the population do not have an equal probability of being included.

What is an unbiased sample?

A sample in which all members of the population have an equal probability of being included.

When can researchers confidently generalize from a sample to a population?

When the sample is representative of the population of interest.

What is external validity?

The extent to which research findings can generalize to the population or other situations of interest.

What sampling terms are associated with external validity?

Representative samples, unbiased samples, probability samples, and random samples.

What is convenience sampling?

Selecting participants who are easiest for the researcher to contact or access.

What is self-selection?

A biased sampling method in which people volunteer to participate.

Where is self-selection especially common?

Online polls.

Why can convenience sampling create bias?

People who are easy to reach may differ systematically from the population.

How can biased sampling affect external validity?

It limits how confidently researchers can generalize findings to the population.

What is a mode effect in survey research?

A difference in responses caused by how a survey is conducted, such as by phone versus online.

How can changing from phone surveys to online surveys affect a trend?

Changes in survey method can create apparent changes in results even when public opinion has not changed.

What example demonstrated a mode effect in the PowerPoint?

Perceived discrimination against gay and lesbian people was reported by 62% in a phone experiment versus 48% in an online poll.

Why did the phone and online estimates differ in the discrimination example?

People were more likely to report discrimination when speaking with an interviewer than when answering privately online.

What is a sampling frame?

A list of the members of a population from which a sample can be selected.

What is an element in sampling?

Each individual member of the population.

What is the relationship between a sampling frame and a sample?

The sample is a subset of the population selected from the sampling frame.

What should researchers consider when defining a population?

Accessibility, availability of a complete list, reading level, languages, cooperation, and geographic restrictions.

What should researchers consider when planning a sample?

Who will respond, whether everyone can be sampled, contact information, ability to locate participants, and anticipated response rate.

How should researchers choose participants for a study?

They should choose participants appropriate to the research question and the population they want to represent.

What is probability sampling?

A sampling approach in which population members have a known chance of selection; the slides describe equal likelihood.

What is nonprobability sampling?

A sampling approach in which population members do not have an equal likelihood of selection.

Which sampling approach generally better supports representativeness?

Probability sampling.

What are the probability sampling methods covered in the PowerPoint?

Simple random, systematic, cluster, multistage, and stratified random sampling, plus oversampling.

What are the nonprobability sampling methods covered in the PowerPoint?

Convenience, quota, purposive, and snowball sampling.

What is simple random sampling?

Selecting participants randomly so each population member has an equal chance of selection.

What is an example of simple random sampling?

Using a random number generator to select students from a complete class list.

What is systematic sampling?

Selecting participants at a regular interval after choosing a starting point.

How does systematic sampling work in the class example?

Start with the fifth person and select every third person until the desired sample size is reached.

What is the difference between simple random and systematic sampling?

Simple random sampling selects individuals randomly; systematic sampling selects individuals at regular intervals.

What is cluster sampling?

Randomly selecting groups, or clusters, and including every individual in each selected cluster.

What is an example of cluster sampling?

Randomly selecting 100 high schools and including every student from those schools.

What is a cluster in sampling?

A naturally occurring group of people, such as a school.

What is multistage sampling?

A method that selects random clusters first and then randomly selects individuals within those clusters.

What are the two stages of multistage sampling?

Stage 1: Randomly select clusters. Stage 2: Randomly select people within those clusters.

What is an example of multistage sampling?

Randomly select 100 high schools, then randomly select students from each selected school.

What is the difference between cluster and multistage sampling?

Cluster sampling includes everyone in selected clusters; multistage sampling selects only some individuals from those clusters.

What is stratified random sampling?

Dividing a population into demographic categories, or strata, and randomly selecting individuals from each category.

Why use stratified random sampling?

To ensure important subgroups are represented in the sample.

What are examples of strata?

Race, gender, or other demographic categories.

What is an example of stratified random sampling?

Randomly selecting Canadians of South Asian descent and other Canadians in proportions matching the population.

How does stratified random sampling help represent a population?

It samples from each subgroup in proportions that reflect the population.

What does strata mean in sampling?

Categories or subgroups into which a population is divided.

What is oversampling?

A variation of stratified random sampling in which one or more groups are sampled in greater numbers than their population proportions.

Why might researchers oversample a group?

To obtain enough participants from a smaller subgroup to make reliable statistical estimates.

What is an example of oversampling?

In a sample of 1,000 Canadians, selecting 100 South Asian Canadians even though they represent 4% of the population.

How is oversampling different from proportional stratified sampling?

Oversampling deliberately includes more people from a subgroup than its proportion in the population.

What must researchers consider when interpreting an oversampled group?

The sample's subgroup proportions do not match the population proportions, so weighting may be needed for population estimates.

What is random sampling?

Selecting a sample randomly from a population; it helps increase external validity.

What is random assignment?

Randomly placing participants into different groups in an experiment.

What is the purpose of random assignment?

To help make experimental groups comparable and increase internal validity.

What is the difference between random sampling and random assignment?

Random sampling selects who participates and supports external validity; random assignment determines group placement and supports internal validity.

When is random assignment used?

In experimental designs.

What is an available sample?

A nonprobability sample obtained by asking available or volunteer participants to take part.

What is convenience sampling also called in the slides?

Haphazard sampling.

What is quota sampling?

A method that tries to match the population on certain characteristics but recruits participants through convenience sampling.

How is quota sampling different from stratified random sampling?

Quota sampling uses nonrandom recruitment; stratified random sampling randomly selects individuals within categories.

What is purposive sampling?

Recruiting specific types of people because they are relevant to the research question.

What is an example of purposive sampling?

Recruiting only people who have experienced a particular event to study that experience.

What is snowball sampling?

A method in which participants recommend other people to participate.

How is snowball sampling related to purposive sampling?

It is a variation of purposive sampling that uses participant referrals to recruit more people.

When is external validity especially important?

When researchers make frequency claims about how common something is in a population.

When might external validity be a lower priority?

In some real-world situations or research studies using nonprobability samples, depending on the research goal.

What determines external validity more: sampling technique or sample size?

Sampling technique.

Why does a larger sample not automatically guarantee representativeness?

A large sample can still be biased if participants are selected unrepresentatively.

What happens to estimates when random samples are smaller?

They tend to be less stable and have larger margins of error.

What is a margin of error?

The amount an estimate from a sample may differ from the true population value due to sampling uncertainty.

What is the margin of error for a random sample of 2,000?

Approximately plus or minus 2 percentage points.

What is the margin of error for a random sample of 1,500?

Approximately plus or minus 3 percentage points.

What is the margin of error for a random sample of 1,000?

Approximately plus or minus 3 percentage points.

What is the margin of error for a random sample of 500?

Approximately plus or minus 4 percentage points.

What is the margin of error for a random sample of 200?

Approximately plus or minus 7 percentage points.

What is the margin of error for a random sample of 100?

Approximately plus or minus 10 percentage points.

What is the margin of error for a random sample of 50?

Approximately plus or minus 10 percentage points.

What is the general relationship between sample size and margin of error?

Larger random samples generally have smaller margins of error.

What are the four main topics in Chapter 7: Sampling?

Populations and samples, biased samples, probability sampling, and nonprobability sampling.