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EPPP 2019 > Research Design and Statistics > Flashcards

Research Design and Statistics Flashcards

1
Q

Pearson r coefficent is used to

A

meausure the linear relationship between two continuous variables

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2
Q

Eta coefficient is used to

A

estimate strength on non-linear relationship between two continuous variables

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3
Q

Spearman rho is used to

A

measure the relationshipt between two sets of ranked data

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4
Q

Biserial

A

Used to measure the relationship between one continuous and one artificially-made dichotmous variable

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5
Q

Point Biserial

A

Used to measure the relationship between one continuous variable and one dichotmous variable

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6
Q

Tetrachoric coefficent

A

used to measure the relationship between two dichotomous variables

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7
Q

Phi coefficent

A

used to measure the relationship between two dichotomous variables

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8
Q

Mulitiple predictors and a single criterion =

A

Multiple regression

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9
Q

Analysis that determines which continous variables discriminant between 2+ naturally occurring groups =

A

discriminant function analysis

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10
Q

Using multiple predictors to sort individuals into 3+ criteron groups

A

Multiple discriminant analysis

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11
Q

What factor analysis is determine variables/components that account for total variance in scores

A

Principle component analysis

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12
Q

Rosenthal Effect or Pygmalion Effect

A

high expectations lead to increased performance

(e. g., Teachers and gifted students)
* Threat to internal validity*

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13
Q

Demand Effect

A

Participants guess what answers experimenters want

Threat to External Validity

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14
Q

Hawthorne Effect

A

Subjects behave different just because they are involved in research
(i.e. lightbulbs experiment)

Threats to External Validity

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15
Q

Threats to Internal Validity

A

History

Maturation

Selection

Experimenter Bias

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16
Q

History

Threat to internal validity

A

Any external event that affects scores or status on the dependent variable

(ex. previous Bullying intervention in classroom A)

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17
Q

Maturation

Threat to Internal Validity

A

Any internal (biological or psychological) change that occurs in subjects while the experiment is in progress and systematically effects DV

(i.e., intellectual development between pre and post)

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18
Q

What are some techniques to control for threats to internal validity?

A

Random Assignment

Blocking

Matching

ANCOVA

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19
Q

Selection

Threat to Internal Validity

A

Pre-existing subject factors that account for scores on the DV

(ex. Class A is naturally more intelligent than Class B)

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20
Q

Standard deviation is…

A

square root of the variance

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21
Q

In an normal distribution, the percent of the population that falls between

-1sd to 1sd

A

68%

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22
Q

68-95-99 rule

A

Population that falls between a

1sd–2sd–3sd

on a normal curve

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23
Q

z-score of +3 is equivalent to what percentile rank?

A

99.9 percentile rank or cutoff of .1%

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24
Q

z-score of +2 is equivalent to what percentile rank?

A

98 percentile rank or cutoff of 2%

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25
z-score of +1 is equivalent to what percentile rank?
84% PR or cutoff point for 16%
26
z-score of -1 is equal to what percentile rank/cutoff score?
16% PR or cutoff for the bottom 16%
27
Z scores are
raw scores stated in standard deviation terms
28
How do you calculate the standard error of the mean?
SEmean= SD/Square root of N
29
What is the standard error of the mean?
How far the **sample mean** can be expected to **deviate** from the **corresponding population mean**
30
Beta means
probability of Type II error
31
Beta means
probability of Type II error
32
Power means
rejecting the null when it is indeed false (avoiding Type II error)
33
Type II error
retaining a **false** null (there was an effect and you missed it)
34
Type I error
rejecting a **true** null (saying there is an effect when there is not)
35
Assumptions of parametric tests
Normal Distribution Homogeniety of Variance Independence of Observations
36
Which assumption of parametric tests is not robust?
Independence of Observations
37
Alpha means...
the probabibility of making Type I error
38
How do you combat threats to internal validity?
Random Assignment to groups Matching Blocking
39
Matching
ensures **equivalency** in an extraneous variable
40
Blocking
determines effect of extraneous variably by making it an IV
41
Examples of non-parametric tests
Chi-squared Mann-Whitney U Wilcoxin Matched-Pairs Test Kruskal Wallis Test
42
Parametric Tests
t-tests one way ANOVA factorial ANOVA MANOVA
43
types of T-tests
one-sample t-test independent samples correlated samples
44
One sample t-test
compare a sample mean to a population mean
45
If you are comparing **two means** you would use a \_\_\_\_\_\_\_\_\_\_
t-test
46
You use an Independent samples t-test ...
when you want to compare means obtained from two independent samples
47
You use a correlated t-test...
when you want to compare means of two correlated samples (pre-post test design)
48
You use a one-way ANOVA when...
there is one IV with 3+ levels
49
The F statistic in ANOVA represents
the ratio of between group variance to within group variance
50
You use a factorial ANOVA when...
you have multiple IV's and one DV
51
What a **factorial ANOVA** yields **both** significant **main and interaction effect** what does this mean?
That the main effects do not generalize to all situations (the iV acts differently at different levels of another IV)
52
When do you use a MANOVA
Analyze data from studies with **multiple DV's (outcomes)** *reduces Type I error as you avoid running seperate ANOVA's for each DV*
53
Chi-square test is used to analyzed what data?
Nominal
54
A **chi-square** test compares frequencies of **observations** under **nominal categories** to...
**frequencies** expected **under the null** hypothesis
55
Mann-Whitney U is used to compare two IV's to...
DV measured with **rank-order** data *Alt. to t-test for independent samples*
56
Wilcoxin Matched Pairs Test is used to....
compare **two correlated groups** to a **DV** measure in **rank-ordered** data *alt. to t-test for correlated samples*
57
When do you use a Kruskal Wallis test
when you want to compare **2+ IV's** on a **DV with rank-ordered** data *alt. to ANOVA*
58
What three non-parametric tests use rank-ordered DV data
Mann Whitney U (2 independent groups) Wilcoxin Matched-Pairs (2 corr. groups) Kruskal Wallis Test (2+ independent groups)
59
Mann Whitney is like
an independent t-test; only uses 2 independent **groups (levels)**
60
Wilcoxin Matched-Pairs test is similar to a...
correlated t-test. Uses two correlated groups
61
Kruskal Wallis is similar to an...
Anova; uses 2 or more independent groups
62
What posthoc test protects best against Type I error?
Scheffe's
63
What posthoc test should you use for pairwise comparisons?
Tukey
64
Internal Validity
ability to determine if there is a causal relationship between IV and DV
65
External Validity
Ability to generalize the results of the study to other people, settings, and conditions
66
Types of random sampling
Stratified random sampling--take a random sample from each subgroup of the total target population Cluster Sampling --sample a naturally occuring group of individuals that represent the target population
67
Ways to increase external validity?
Random selection (random sampling) Naturalistic Research Single-Double Blind Research Counterbalancing
68
Threats to external validity are...
Selection x Treatment History x Treatment Testing x Treatment Demand Characteristics Hawthorne Order effects
69
T-tests cannot be used if there are more than ____ groups to compare
2 *T-test means two*
70
What is an eigenvalue?
how much variability a particular factor is accounting for in the other studied variables (a factor's strength or explanatory power)
71
In a PCA, factors are always\_\_\_\_\_\_\_ uncorrelated or correlated?
uncorrelated/independent
72
The relationship between predictor variables and criterion in a multiple regression model is known as
multiple R or multiple correlation coefficient
73
Other Correlational Techniques include
Canonical Correlation Discriminant Function Analysis Logistic Regression Multiple Cutoff Partial Correlation
74
Canonical Correlation
multiple criterion and multiple predictor variables
75
Discriminant Function Analysis
Scores on several variables are combained to predict group membership (backwards from MR)
76
Predictor variables in a discriminant function analysis require \_\_\_\_\_\_\_\_
Differential Validity --each predictor must have a different correlation with each criterion variable
77
Logistics Regression *Alternative to discriminant function analysis*
* Used when assumptions of homogeniety and normality are not met * Can use nominal or continous data * Primarily used in research with dichotomous criterion
78
Path analysis vs. LISREL: what are the differences? *Types of SEM*
one-way causal flow vs. one/two-way observed variables only vs. latent and observed
79
When should you use a Contingency coefficient
when both variables are nominal (name) (ex. categories)
80
Contigency coefficient vs. phi coefficent
nominal vs. dichotomous variables
81
Random assignment vs. Random selection
Random assignment is for external validity Random selection is for internal validity
82
Trend analysis is used in what type of research design?
Repeated measures *measures the nature of an effect and whether the relationship is linear or non-linear*
83
Trend analysis requires what type of IV and DV variables?
Interval or Ratio (quantitative)
84
Formula for standard error of the mean
sd/sqrt(N)
85
A change in the raw score at the middle of a distribution will result in ***[greater/lesser]*** c**hange in percentile rank** compared to a change in raw score at the end of the distribution
greater
86
Raising the cutoff score on a predictor will
decrease false positives decrease true positives (move vertical line to the right)
87
Item response theory
is typically applied to develop culture faire tests
88
Minimum F value in an Anova is
1
89

EPPP 2019 (10 decks)

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