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**DQE > Stats 2 First Exam > Flashcards

Stats 2 First Exam Flashcards

1
Q

Descriptive research

A

Describes population we are studying

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2
Q

Central tendency demonstrates

A

Mid-points

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3
Q

Spread

A

Range, SD, D, etc.

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4
Q

Frequency

A

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

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5
Q

Inferential research

A

Infer from the sample to the population

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6
Q

Parameter

A

Value corresponding to population

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7
Q

Statistic

A

Value corresponding to sample

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8
Q

Historical research

A

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

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9
Q

Regression

A

Type of correlation research positing temporal order of variable

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10
Q

Causal-Comparative

A

Allows for making causal statements

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11
Q

Ex-post facto

A

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

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12
Q

Pre-experimental designs

A

Are limited. Example: One-shot case study

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13
Q

Quasi-experimental design

A

Control group and experimental group but no randomization.

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14
Q

True experimental design

A

Researcher manipulation and randomization

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15
Q

Meta-analyses

A

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

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16
Q

Continuous variable

A

Allows values in-between

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17
Q

Categorical variable

A

Groups, no in-between

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18
Q

Fixed variable

A

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

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19
Q

Random variable

A

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

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20
Q

Multivariate

A

More than one DV

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21
Q

Univariate

A

One DV

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22
Q

Multiple regression

A

More than one IV

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23
Q

Factorial

A

More than one IV with analysis of variance

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24
Q

Sampling distribution

A

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

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25
Q

Central limit theorem

A

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

26
Q

Mean distribution

A

Unit normal curve

27
Q

Chi square distribution

A

Summation of variances

28
Q

T distribution

A

Difference between means divided by standard errors

29
Q

F distribution

A

Variances compared as ratio

30
Q

Why is normal curve mother of all curves?

A

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

31
Q

When decreasing alpha,

A

Beta increases, power decreases

32
Q

When decreasing beta,

A

Alpha gets bigger

33
Q

When increasing alpha

A

Power increases

34
Q

How to increase power?

A
  1. Bigger sample 2. Stronger tx/effect 3. Improve measurement
35
Q

Correlational research

A

Show how y changes when x changes. No causality

36
Q

Regression

A

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

37
Q

Causal Comparative

A

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

38
Q

Wording Cues for Determining Category of Research: Versus

A

Causal-comparative

39
Q

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

A

Experimental or causal-comparative

40
Q

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

A

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

41
Q

Wording Cues for Determining Category of Research: Relationship

A

Correlation

42
Q

One sample tests compare

A

Sample to population. Does sample match?

43
Q

Assumption: I

A

Independence

44
Q

Assumption: N

A

Normality of error term (not the sample term)

45
Q

Assumption: H

A

Homogeneity - equivalent variances (SD, etc.)

46
Q

Assumption: R

A

Randomness of error term

47
Q

Assumptions of I & R come from…

A

Methodology and sampling plan

48
Q

Assumptions H & N…

A

May be tested

49
Q

Questions of significance testing

A
  1. Is there a difference? 2. Where is it? 3. How big is it/does it matter?
50
Q

Effect size/strength of association

A

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

51
Q

What is ANOVA?

A

Ratio of variability between groups to the variability within groups

52
Q

SPSS output demonstrating test of homogeneity

A

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

53
Q

Use Tukey test if…

A
  1. Have found significance. 2. Have = n 3. Are conducting pairwise comparisons
54
Q

Use Scheffe test if…

A
  1. Multiple cells 2. Unequal n pairwise
55
Q

Helmert contrast

A

1st vs else

56
Q

Difference contrast

A

“reverse Helmert” Last vs. else

57
Q

What are statistics of strength of association?

A
  1. Eta squared 2. Omega squared
58
Q

Eta squared

A
  1. Use with unequal n 2. SSH/SSTotal 3. Is an estimate
59
Q

Omega squared

A
  1. For = n 2. SSB - dfb * MSW (error term) / MSW + SST 3. More precise
60
Q

f =

61
Q

MSh / MSe =

A

SSH / dfH / SSE / dfe

**DQE (27 decks)

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