Basic Principles Re: Methods, Data, & Statistical Results

Question 1

Dependent variables (DVs) are known as what?

Answer 1

The outcome variables- values that constitute results of the study

Question 2

Why are they called dependent variables?

Answer 2

Variation in these variables follows from or depends on other factors

Question 3

True or False: The DV is measured, but not directly controlled

Answer 3

True

Question 4

Independent variables are referred to as what?

Answer 4

Variable being controlled by the experimenter

Question 5

What is the purpose of the IV?

Answer 5

To determine if the IV leads to variation in the DV

Question 6

What are the two ways an IV can be created?

Answer 6

1. Manipulation; Changing levels of the IV
2. Selection; choosing people of certain ages

Question 7

Do all variables have to be divided into IV and DVs?

Answer 7

No; some studies can study the variations in one measure which relate to the variations in others

Question 8

Variables can also be referred to as

Answer 8

Factors

Question 9

The values that variables take are called

Answer 9

Levels

Question 10

When studies do fit the IV and DV mold, what can we use to describe them?

Answer 10

Factor terminology

Question 11

The Brownell et al. (2009) study contained two independent factors (adult verbalization, child age), each of which had two levels (silent, verbalization) (18-, 25-month-olds). What would this design be called?

Answer 11

2x2 Factorial design

Question 12

In the Brownell et al. (2009) study, it was a 2x2 factorial design. how many groups/conditions did this study have? This reflects the IVs and levels involved within the study.

Answer 12

4 conditions

Question 13

Within a study, what is more important, the main effect or interaction?

Answer 13

The interaction effect

Question 14

What is a main effect?

Answer 14

The overall effect the IV/predictor variable has on the Dv/criterion

Question 15

The 18 months value was .53 and the 25 months value was .56. Was there a main effect?

Answer 15

no

Question 16

the adult silent value was .51 and the adult verbalization was .58. Was there a main effect?

Answer 16

No

Question 17

true or false: A main effect for a variable w/ 2 levels is NOT interpreted the same way as a main effect for a variable w/ 3 levels (or more).

Answer 17

True

Question 18

If there are only 2 groups, what can we know in terms of effects?

Answer 18

We know if they differed via a main effect through t-test

Question 19

If there are 3 groups, can you tell which groups differed from each other?

Answer 19

No, can only tell some differences, but not which specific groups. You must run post-hoc comparison after ANOVA test

Question 20

When can an interaction effect occur?

Answer 20

When there’s more than one causal/predictor variable

Question 21

Interaction effect involves the effect of

Answer 21

One variable differing depending on the level of the second variable

Question 22

A main effect tells us there’s a _______ while an interaction effect tells us theres

Answer 22

simple difference; difference in differences

Question 23

Interaction is often short for

Answer 23

two-way interaction

Question 24

Can an interaction be observed?

Answer 24

Must be statistically tested; as it is more visible and interpretable through figural rather than table, representations (i.e. bar graphs)

Question 25

Interactions are readily dectectable by what?

Answer 25

Non-parallel nature of graphs (bars/lines) across conditions

Question 26

Groups/conditions should be represented by ______ but is usually presented in a ____ bc it is easier to see

Answer 26

bar graphs, line graphs

Question 27

Describe the interaction from the Brownell,Svetlova, and Nichols (2009) study.

Answer 27

The younger group showed a slight decrease in sharing when adults verbalized, while the older group showed more sharing when adults verbalized.

Question 28

true or false: interactions are limited to only experimentally manipulated IVs

Answer 28

False; it can occur among all IVs/PVs (including non-manipulated ones)

Question 29

Are interactions only limited to group designs?

Answer 29

No; can occur among non-manipulated PVs in a correlational design

Question 30

What does variance refer to?

Answer 30

differences in scores on the DV

Question 31

Variance quantifies what?

Answer 31

how spread out the scores of a sample are around their mean

Question 32

When computing the variance of a set of scores, we start by

Answer 32

calculating how far each score is from the mean.

Question 33

Total variance accounted for” or “primary variance

Answer 33

those differences that are accounted for by the IVs/predictors (i.e., explained by the IV/predictor variables)

Question 34

We always say that we want our studies to include a diverse group of people so that we can generalize it to other samples and settings. What kind of validity would this be focusing on?

Answer 34

external validity

Question 35

When a study mainly emphasizes the strength of an effect (i.e., effect size) and the probability (statistical significance) that the results could have been obtained by chance (e.g., there is not really an effect/association), what kind of validity is this?

Answer 35

Statistical validity

Question 36

In a study testing teacher autonomy support and school readiness, the study claimed that teacher A-S had an effect on a child's school readiness, when in reality, it did not. What type of statistical error would this be?

Answer 36

Type 1 error; false positive

Question 37

In a study testing school readiness and temperament, the study found that temperament DID NOT have an effect on a child's school readiness, when it actually did. What type of statistical error would this be?

Answer 37

Type 2 error; false negative

Question 38

What are the effect sizes and what can they be described as?

Answer 38

.20 -> small .50 -> medium .80 -> large

Question 39

When a study wants to address the extent to which one variable (X) has an effect on another variable (Y) rather than some other variable (C), what kind of validity would this be?

Answer 39

Internal validity

Question 40

To move from the language of association to the language of causality, a study must satisfy several criteria:

Answer 40

a) establish the two variables are correlated; correlation cannot be 0 (EASIEST) b) study must show the causal variable came first (i.e. temporal precedence); HARDEST c) establish no other/alternative exist for the relationship (i.e., study has internal validity); HARDEST

Question 41

What does internal validity first ask?

Answer 41

if the study was able to achieve temporal precedence

Question 42

What does internal validity ask after achieving temporal precedence?

Answer 42

whether the study controlled for alternative explanations (e.g., confounding variables)

Question 43

What are ways to control for confound variables?

Answer 43

1) RA participants to groups/conditions; between-subjects experiment 2) assigning all conditions to every participant; within-subjects experiment 3) correlational study & statistically control for alternative explanations/confounds by using multiple regression

Question 44

If your plausible alternative explanations for findings have NOT been removed/controlled for, what can you not do?

Answer 44

Be certain the variability recorded in the DV is due to the variability in the IV

Question 45

True or false: it is impossible to control for all validities at once

Answer 45

True

Question 46

Explain what happens between internal validity and external validity when trying to achieve both.

Answer 46

When you try to prioritize and control the experiment more, you achieve more internal validity, but compromise external validity due to the controlled environment.

Question 47

If your goal is to test a causal claim, what validity would you prioritize?

Answer 47

Internal validity

Question 48

if your goal is show that your claim can be generalized to multiple populations, what validity would you strive for?

Answer 48

External validity

Question 49

In most research, what should we prioritize and why?

Answer 49

Internal validity; because if we don't have valid data, we cannot even generalize it

Question 50

What are the 3 ways to control?

Answer 50

1) control over the iv/causal variable 2) control over setting 3) control over preexisting diff among participants

Question 51

For the 3 controls; correlational studies _______ what? experimental studies ______ what?

Answer 51

don't have these controls mess up these controls

Question 52

In Kliegel et al. (2007), they presented the instructions and stimuli for the familiar and novel conditions in the same way for all participants. What kind of control would this be?

Answer 52

Control over the IV

Question 53

What must be true of control over the IV/causal variable?

Answer 53

No unintended deviations Critical elements must be the same

Question 54

How do you achieve control over setting?

Answer 54

1) hold all the factors constant for participants (same time, noise, etc) 2) disperse variations in other factors randomly (different times, experimenters, materials)

Question 55

T or F: possible to control a variable by making it the same for all participants.

Answer 55

False; alternative is to vary acoss groups

Question 56

In Brownell et al. (2009) they used the same testing room for all participants. What kind of control would this be?

Answer 56

Control over setting

Question 57

In Kliegel et al. (2009), they varied the time of testing randomly across groups. What kind of control did they achieve?

Answer 57

control over setting

Question 58

How do you control over pre-existing differences among subjects?

Answer 58

1) random assignment (between groups) 2) matching variables 3) giving each participant every condition (within subjects)

Question 59

In Kliegel et al. (2009), they randomly assigned half of the participants to the familiar condition and the other half to the novel condition. what kind of control is this?

Answer 59

Control over pre-existing differences among subjects

Question 60

What are subject variables aka "classification" variables?

Answer 60

variables that are NONMANIPULATED; taken as they naturally are

Question 61

How do you control for subject variables aka classification variables?

Answer 61

Through selecting people w/ that characteristics

Question 62

Age, income/SES, gender, temperament, IQ are all examples of what kind of variable?

Answer 62

subject variables

Question 63

How do we create "causal variables" for subject variables?

Answer 63

Through selection

Question 64

For research w/ non-manipulated variables, what is the limit for construct validity?

Answer 64

a potential problem; we are unsure what the true construct is bc each variable is multiple factors

Question 65

For research w/ non-manipulated variables, what is the limit for internal validity?

Answer 65

You have no control over the IV/PV; therefore you cannot assume equivalence

Question 66

For research w/ non-manipulated variables, what is your solution to controlling for pre-existing differences among subjects?

Answer 66

1) control through selection of participants w/ only one level of characteristic (not really feasible) 2) measure for the confound and see if it correlates w/ your causal variable (IV/PV) and your DV

Question 67

When is the C variable a confound?

Answer 67

ONLY if it systematically varies w/ your PV and your DV

Question 68

True or False; A variable is a confound if it does not vary

Answer 68

False; only a confound if it varies

Question 69

If the c variable does vary w/ your DV & causal variable, what do you do?

Answer 69

Control for it using multiple regression

Question 70

Examining ONLY 5 year old toddlers in a study would be what kind of comparison?

Answer 70

Implicit age comparison

Question 71

True or False; finding a "genuine change with age" means literal age produces the change

Answer 71

False; Only means that variables that are regularly & naturally associated w/ age produce the change

Question 72

True or False; researchers study ALL the people they're interested in.

Answer 72

False; test only samples

Question 73

How can researchers ensure that a sample is representative of the population to which they wish to generalize?

Answer 73

1) define the scope of generalization (i.e. the population of interest) 2) decide how to select from the population

Question 74

If all members of the population really are equally likely to be selected, what method is this?

Answer 74

random sampling

Question 75

For a study of U.S. undergraduates, researchers draw 5% of each class year. What kind of sampling method is this?

Answer 75

Stratified sampling

Question 76

For a study of high schoolers in which comparisons among ethnic groups are of interest, suppose that Asian Americans constitute 3% of the high school population in your city. Researchers choose to sample 6% of the population to get a larger subgroup. What kind of sampling method is this?

Answer 76

oversampling

Question 77

Where do researchers tend to draw their samples from realistically?

Answer 77

Within their communities in which they live/work and may only sample a few.

Question 78

Selection of samples primarily on the basis of availability or cooperation is referred to as

Answer 78

convenience sampling

Question 79

Samples obtained via ___________ will not be perfectly representative of the broader population with respect to variables like race, ethnicity, region, education, social class, or even age.

Answer 79

convenience sampling

Question 80

Although many samples depart from representation; what is not threatened?

Answer 80

external validity bc the deviations fr/ representation do not have any plausible effect on generalizability

Question 81

Finding a representative pool of potential participants is a good starting point, but… the REAL question is how well the final sample reflects the initial pool?

Answer 81

1) initial pool solicited 2) % agreed & how they differ from initial pool 3) % retention of people & how they initial from initial pool