Stats 2 First Exam

Question 1

Descriptive research

Answer 1

Describes population we are studying

Question 2

Central tendency demonstrates

Answer 2

Mid-points

Question 3

Spread

Answer 3

Range, SD, D, etc.

Question 4

Frequency

Answer 4

Number of times it occurs, percent/portion of time it occurs: n, f, p

Question 5

Inferential research

Answer 5

Infer from the sample to the population

Question 6

Parameter

Answer 6

Value corresponding to population

Question 7

Statistic

Answer 7

Value corresponding to sample

Question 8

Historical research

Answer 8

Looking at past using causal comparative, descriptive, and inferential analysis

Question 9

Regression

Answer 9

Type of correlation research positing temporal order of variable

Question 10

Causal-Comparative

Answer 10

Allows for making causal statements

Question 11

Ex-post facto

Answer 11

Identify settings with differing characteristics and assume difference in results is due to different characteristics

Question 12

Pre-experimental designs

Answer 12

Are limited. Example: One-shot case study

Question 13

Quasi-experimental design

Answer 13

Control group and experimental group but no randomization.

Question 14

True experimental design

Answer 14

Researcher manipulation and randomization

Question 15

Meta-analyses

Answer 15

Aggregate results from many different studies (frequently based on effect sizes)

Question 16

Continuous variable

Answer 16

Allows values in-between

Question 17

Categorical variable

Answer 17

Groups, no in-between

Question 18

Fixed variable

Answer 18

Allows only certain range (e.g., ages 20-40)

Question 19

Random variable

Answer 19

Allows all possibilities. Each has equal and independent chance of occurring

Question 20

Multivariate

Answer 20

More than one DV

Question 21

Univariate

Answer 21

One DV

Question 22

Multiple regression

Answer 22

More than one IV

Question 23

Factorial

Answer 23

More than one IV with analysis of variance

Question 24

Sampling distribution

Answer 24

Graph statistics of infinite number of samples (graph of means)

Question 25

Central limit theorem

Answer 25

Graph of means will be equal to population mean (The mean of the means (Samples) is the mean (population mean)

Question 26

Mean distribution

Answer 26

Unit normal curve

Question 27

Chi square distribution

Answer 27

Summation of variances

Question 28

T distribution

Answer 28

Difference between means divided by standard errors

Question 29

F distribution

Answer 29

Variances compared as ratio

Question 30

Why is normal curve mother of all curves?

Answer 30

Given an infinite number of samples for any statistic, all will collapse to normal curve

Question 31

When decreasing alpha,

Answer 31

Beta increases, power decreases

Question 32

When decreasing beta,

Answer 32

Alpha gets bigger

Question 33

When increasing alpha

Answer 33

Power increases

Question 34

How to increase power?

Answer 34

1. Bigger sample 2. Stronger tx/effect 3. Improve measurement

Question 35

Correlational research

Answer 35

Show how y changes when x changes. No causality

Question 36

Regression

Answer 36

No causality, but do want predictability. Establish equation to predict y. Statistical tool, not type of research-- correlation is the type of research. Research question is predictability

Question 37

Causal Comparative

Answer 37

Attempt to make causal interpretation of the data. Further than relation, further than prediction, this causes the effect.

Question 38

Wording Cues for Determining Category of Research: Versus

Answer 38

Causal-comparative

Question 39

Wording Cues for Determining Category of Research: Effectiveness/ effects of

Answer 39

Experimental or causal-comparative

Question 40

Wording Cues for Determining Category of Research: Positive and negative effects

Answer 40

Experimental or causal-comparative (depending on what was done)

Question 41

Wording Cues for Determining Category of Research: Relationship

Answer 41

Correlation

Question 42

One sample tests compare

Answer 42

Sample to population. Does sample match?

Question 43

Assumption: I

Answer 43

Independence

Question 44

Assumption: N

Answer 44

Normality of error term (not the sample term)

Question 45

Assumption: H

Answer 45

Homogeneity - equivalent variances (SD, etc.)

Question 46

Assumption: R

Answer 46

Randomness of error term

Question 47

Assumptions of I & R come from...

Answer 47

Methodology and sampling plan

Question 48

Assumptions H & N...

Answer 48

May be tested

Question 49

Questions of significance testing

Answer 49

1. Is there a difference? 2. Where is it? 3. How big is it/does it matter?

Question 50

Effect size/strength of association

Answer 50

Percent of variability in DV that can be attributed to variability in IV

Question 51

What is ANOVA?

Answer 51

Ratio of variability between groups to the variability within groups

Question 52

SPSS output demonstrating test of homogeneity

Answer 52

Levene's. Non-significant means assumption of homogeneity upheld.

Question 53

Use Tukey test if...

Answer 53

1. Have found significance. 2. Have = n 3. Are conducting pairwise comparisons

Question 54

Use Scheffe test if...

Answer 54

1. Multiple cells 2. Unequal n pairwise

Question 55

Helmert contrast

Answer 55

1st vs else

Question 56

Difference contrast

Answer 56

"reverse Helmert" Last vs. else

Question 57

What are statistics of strength of association?

Answer 57

1. Eta squared 2. Omega squared

Question 58

Eta squared

Answer 58

1. Use with unequal n 2. SSH/SSTotal 3. Is an estimate

Question 59

Omega squared

Answer 59

1. For = n 2. SSB - dfb * MSW (error term) / MSW + SST 3. More precise

Question 60

f =

Answer 60

MSh / MSe

Question 61

MSh / MSe =

Answer 61

SSH / dfH / SSE / dfe