Psych 100

Front 1

Institutional Review Board (IRB)

Back 1

Committee responsible for interpreting ethical principles and ensuring that research using human participants is conducted ethically.

Front 2

Debriefing

Back 2

Once the participants are done with the experiment, they are told what the experiment was about, its purpose, etc.

Front 3

Informed Consent

Back 3

A written document that clarifies what the participant will do in such experiment, the risks ( there should be none) and the agreement of the participant to be in such experiment.

Front 4

Deception

Back 4

Researchers withheld some details of the study from participants - Deception through omission; IN some cases, they actively lied to them - deception through commission

Front 5

The 5 Biased sampling techniques

Back 5

1. Convenience sampling:

- Uses samples that are chosen merely on the basis of who is easy to access.

2. Purposive sampling:

- Used when researchers want to study only certain kinds of people, they only recruit those particulars participants.

3. Snowball Sampling:

- Participants are asked to recommend a few acquaintances for the study.

4. Quota sampling:

- When there's a target number for each category in the sample ( e.g: 80 Asian Americans, 80 Latinos and 80 African Americans)

Front 6

The 6 Unbiased sampling techniques

Back 6

1. Simple random sampling:

- The most basic form of probability sampling is simple random sampling

2. Cluster sampling:

- clusters of participants within a population of interest are randomly selected, and then all individuals in each selected cluster are used.

3. Multistage sampling:

- 2 random samples are selected: a random sample of clusters, then a random sample of people within those clusters.

4. Stratified random sampling:

- The researcher selects particular demographic categories and on purpose and then randomly selects individuals within each of the categories.

5. Oversampling:

- The researcher intentionally over represents one or more groups.

6. Systematic sampling:

- Using a computer or a random number table, the researcher starts by selecting two random numbers - say 4 and 7.

Front 7

Why is it important how a sample is obtained than how many are obtained?

Back 7

Because if it's all biased sampling, then the results won't be accurate/ will be incorrect. A bias sample doe not give an accurate representation.

Front 8

Which of the 4 major validities does sampling address?

Back 8

Statistical, Internal, External

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Front 9

The 5 major questions which should be asked when assessing the statistical validity of an association claim.

Back 9

1. What is the effect size:

- The effect size describes the strength of the association

2. Is the correlation statistically significant?

- Refers to the conclusion a researcher reaches regarding how likely it is they'd get a correlation of that size by just chance, assuming that there's no correlation in the real world

3. Could outliers be affecting association:

- Depending on where the outlier sits in relation to the rest of the sample, a single outliner can have a strong effect on the correlation coefficient

4. Is there restriction of range:

- If there is not a full range of scores on one of the variables in the association, it can make the correlation appear smaller than it really is.

5. Is the association curvilinear:

- The relationship between two variables is not a straight line. Eg: the relationship might be positive up to a point, and then become negative.

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Internal validity - Be able to explain why one cannot make a causal conclusion from association claim by addressing the 3 causal conditions: Covariation, Temporal precedence and internal validity (3rd variable)

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1. Covariance of cause and effect:

- There must be correlation, or association, between the cause variable and the effect variable.

2. Temporal precedence:

The causal variable must precede the effect variable; it must come first in time.

3. Internal Validity:

- There must be no plausible alternative explanations for the relationship between the two variables.

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External Validity – be able to assess how well an example correlation will generalize to differentpopulations and different situations by analyzing HOW the sample was achieved.

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1. The size of the sample does not matter as much as the way the sample was selected from the population of interest.

Front 12

Understand what a Moderator is and how it is different from a third variable.

Back 12

The relationship between 2 variables changes depending on the level of another variable, that other variable is called a moderator.

eg: People that scored high on extroversion were also more likely to be recorded as talking during the sampling periods.

For men extroversion is not related to having a higher percentage of group conversations, For women though, extroversion is positively related to having more group conversations.

In this example you'd say that gender moderates the association between extroversion and group conversations.

Front 13

Be able to explain how experiments support causal statements (compared to a correlational study)?

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1. Covariance:

- Is the causal variable related to the effect variable? Are distinct levels of the independent variable associated with different levels of the dependent variable?

2. Temporal precedence:

- Does the causal variable come before the effect variable in time?

3. Internal validity?

- Are there alternative explanations for the results?

Front 14

What is the minimum requirement for a study to be labeled an experiment (regardless of whether it is aGOOD experiment or not)?

Back 14

Researchers manipulate one variable and measure another.

Front 15

Understand why systematic variance is bad. A variable that systematically varies along with the IV iscalled what?

Be able to describe an example experiment that has systematic variance and explain why the confounding variable makes it difficult to make an accurate conclusion.

Back 15

It can be bad because it could affect the results of the experiment. Systematic Variability.

Ex: the pasta is served to both groups ( small bowl + big bowl ) by the assistants. The assistants then can be friendly or serious towards one of the specific groups.

Front 16

Why is unsystematic variance not so bad? What technique do researchers use to ensure that participantvariables are distributed unsystematically?

Back 16

Because it is evenly across the groups.

Random sampling/Assignment?

Front 17

Understand the 3 threats to internal validity and how they are controlled for by researchers.

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1. Did the experimental design ensure that there were no design confounds, or did some other variable accidentally covary along with the intended independent variable?

2. If the experimenters used an independent-group design, did they control for selection effects by using random assignment or matching?

3. If the experimenters used a within-groups design, did they control for order effects by counterbalancing?

Front 18

Know the 2 Independent and within-groups designs and the advantages/disadvantages of each.

Back 18

1. Advantages: ensures that he participants in the two groups will be equivalent; after all they are the same participants.

2. Disadvantages: potential for order effects, might not be possible or practical and when people see all levels of the independent variable, changing the way they would normally act.

Front 19

Know the section, “Interrogating Causal Claims with the Four Validities.” Be able to assess the strengthof a causal conclusion when given an example experiment.

Back 19

1. construct validity: How well were the variables measured and manipulated?

2. External Validity: To whom or what can the causal claim generalize?

3. Statistical validity: How well do the data support the causal claim?

4. Internal validity: Are there alternative explanations for the outcome?

Front 20

Understand the 6 threats to internal validity for a one-group pretest/posttest design and how to controlfor them.

Back 20

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