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Comps - Research Makeup Flashcards

1
Q

What is the IV?

A

The variable that is being manipulated

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2
Q

What is the DV?

A

The variable being measured

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3
Q

What is a covariate?

A

An additional variable that is secondary to the IV and DV that is being statistically controlled for because it is thought to have some sort of effect on the DV

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4
Q

What is a confounding variable?

A

A variable other than the independent variable (or treatment) on which the participants in one experimental condition differ systematically from participants in other experimental conditions

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5
Q

What is an extraneous variable?

A

Any variable other than the independent variable (or treatment) that causes changes in the dependent variable (or outcome)

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6
Q

What is a control group?

A

The group that is receiving no treatment or a placebo; a group that does not experience any change to the variable being tested

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7
Q

Why is it important to have a control group?

A

To create a benchmark to compare the experimental results to. It allows for study of the effects of the independent variable alone without confounding conditions. Without a control group, it’s hard to determine whether external factors (e.g., time, maturation) influenced the results

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8
Q

What is the null hypothesis?

A

There are no differences/relationships found

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9
Q

What is the alternative hypothesis?

A

There are differences/relationships found

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10
Q

What is power?

A

The probability that we can reject the null hypothesis (1 - beta)

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11
Q

What does more power do?

A

Higher power reduces the risk of Type II errors (failing to reject a false null hypothesis)

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12
Q

How can power be increased?

A

-use homogenous participants
-equal cell sample sizes
-within-participants design
-matching and stratifying
-increase the strength of treatment
-increase the variability of treatment
-larger sample size
-improve measures
-use powerful statistical tests and be sure the assumptions are met
-reduce random setting irrelevancies
-measure and correct for covariates

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13
Q

What is non-random sampling?

A

A method of selecting a sample from a population where the selection is not based on random chance, but rather on factors like convenience, researcher judgment, or specific characteristics, meaning not every member of the population has an equal chance of being chosen, which can introduce bias

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14
Q

What are the different types of non-random sampling?

A

Conveniences, snowball, and purposive sampling

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15
Q

What is convenience sampling?

A

Where participants are selected based on their availability, accessibility, or proximity to the researcher

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16
Q

What is snowball sampling?

A

Existing participants recruit future participants from their social networks

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17
Q

What is purposive sampling?

A

-purposive sampling of heterogeneous instances (PSI-Het)
-drawing a sample that captures the range of values present in the population of interest
-the idea is to develop a sample that is really heterogeneous and broad
-purposive sampling of typical instances (PSI-Typ)
-drawing a sample close to the central tendency of the population of
interest
-the idea is the draw a sample that is close to the average/most typical

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18
Q

What is random sampling?

A

Selects participants for the research on the basis of chance

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19
Q

What are the different types of random sampling?

A

Simple random, cluster, stratified, disproportionate stratified, and systematic random sampling

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20
Q

What is simple random sampling?

A

Each member of the population has an equal chance of being selected; research participants are randomly selected from a list of all members of the population of interest

21
Q

What is cluster sampling?

A

The population is divided into smaller groups, called clusters, and then individuals are randomly selected from these groups

22
Q

What is stratified sampling?

A

It is used when we want to make sure that some characteristic is represented in the sample in the same proportion as it is represented in the population

23
Q

What is disproportionate stratified sampling?

A

Used when the strata differ in size and we want to include enough people from each one to allow us to compare the characteristics of the strata

24
Q

What is systematic random sampling?

A

A desired sample size is assigned, and then a regular interval number is used to decide who will be sampled

25
What does random sampling strengthen and why?
Random sampling strengthens external validity by drawing a representative sample, which increases generalizability from the sample to the population
26
What is a quasi-experimental design?
An experiment in which units are not assigned to conditions randomly
27
Why use a quasi-experimental design?
When random assignment is not feasible due to ethical, logistical, or practical reasons, quasi-experimental designs allow for studying cause-and-effect relationships
28
What is a randomized design?
An experiment in which units are assigned to receive the treatment or an alternative condition by a random process such as the toss of a coin or a table of random numbers
29
Why use a randomized design?
They are considered the most rigorous for establishing cause-and-effect relationships because random assignment reduces selection bias and ensures that groups are comparable at baseline
30
What is random assignment?
Random assignment places people into experimental conditions on the basis of chance
31
What does random assignment strengthen and why?
Random assignment strengthens internal validity by evenly distributing participant characteristics across conditions and thus ruling out the selection threat
32
What is non-random assignment?
A method in research where participants are not allocated to different study groups based on chance (randomly), but instead are assigned based on specific characteristics or factors, which can introduce bias and limit the ability to establish a true cause-and-effect relationship within the study
33
What is inclusion criteria?
Refers to the specific characteristics that a participant or study must possess to be eligible for inclusion in a research stud
34
What is exclusion criteria?
Characteristics that would disqualify a participant or study from being included, even if they meet the inclusion criteria
35
What is the sample size?
The number of individuals or observations included in a research study to represent a population
36
What is pilot testing?
A preliminary study conducted on a small scale before the main research to evaluate the feasibility, design, and procedures of the study
37
What are manipulation checks?
Procedures used in experimental research to confirm that the independent variable has been successfully manipulated as intended
38
What does the analysis find?
If there are any differences between groups
39
What is a post-hoc?
Where the differences between the groups are after finding a significant ANOVA result
40
What are the main types of post-hocs?
Bonferroni Correction or Tukey's HSD
41
What is an effect size?
Measures how large an observed effect is; practical component of inferential statistics (how meaningful the results are)
42
What is a Type I Error?
Rejecting the null hypothesis when it is actually true; conclude you have found a relationship, but there actually is not one (false positive)
43
What is a Type II Error?
Fail to reject the null hypothesis when it is actually true; conclude that there is no relationship, but there actually is one (miss)
44
What is a moderator?
Quantitative or qualitative variable M influences the strength or direction of the relationship between X and Y; Both the IV and the moderator can have significant independent effects on the outcome variable
45
What is a mediator?
Variable M is responsible for the observed relationship between X and Y; Mediators explain the effect of an IV on a DV
46
What is internal validity?
The degree to which the results of the treatment reflect a true cause-effect relationship
47
What is external validity?
The degree to which the results can generalize the cause-effect relationship to other persons, settings, treatments, and measurements
48
What is statistical conclusion validity?
-validity of inferences about the covariance between treatment and outcome (long) -the degree to which the results being drawn from the statistical tests are valid and accurate
49
What is construct validity?
The degree to which the constructs intended to be measured through a particular tool or instrument accurately measures the abstract concept it is intended to measure

Comps (14 decks)

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