N211 Stats Review

Question 1

Independent samples are ____ while dependent samples are ____

Answer 1

unrelated, related

Question 2

Between parametric and non-parametric tests, which are more powerful?

Answer 2

Parametric

Question 3

Between parametric and non-parametric tests, which are more likely to make a Type 2 Error?

Answer 3

Non-parametric

Question 4

The non-parametric equivalent of an independent t-test is:

Answer 4

Mann-Whitney U test

Question 5

The non-parametric equivalent of a paired t-test is:

Answer 5

Wilcoxon Signed-Rank test

Question 6

The non-parametric equivalent of a one-way ANOVA is:

Answer 6

Kruskal-Wallis test

Question 7

The non-parametric equivalent of a one-way repeated measures ANOVA is:

Answer 7

Friedman’s ANOVA

Question 8

What are the 3 requirements for using a chi-square test (sample, data, value)?

Answer 8

• 2 random independent samples
• Data is nominal or ordinal
• Value of each cell must be >5

Question 9

What is the null vs alternate hypothesis for chi-square?

Answer 9

Ho: no difference between 2 groups
Ha: significant difference between 2 groups

Question 10

How do you calculate degrees of freedom for chi-square tests?

Answer 10

Df = (# of rows - 1) x (# of columns - 1)

Question 11

If the X^2 sample is > the critical value, is the result statistically significant? Do you accept or reject the Ho?

Answer 11

Yes, reject Ho

Question 12

What are the 4 requirements for using t-tests (sample, dv, variance)?

Answer 12

• 2 random samples
• Interval or ratio DV
• Normal distribution of DV
• Homogeneity of variance

Question 13

How do you calculated degrees of freedom for t-tests?

Answer 13

Df = (sample size of both groups) - 2

Question 14

For t-tests, is p > or < alpha if Levene’s F value is significant? Does this mean we assume equal variance? Do we accept or reject Ho?

Answer 14

p < alpha, DON’T assume equal variance, reject Ho

Question 15

If t sample is < t critical value, is it significant? Do you accept or reject Ho?

Answer 15

Not significant, accept

Question 16

ANOVAs compare how many sample means?

Answer 16

2+

Question 17

What is the null and alternative hypothesis for ANOVAs?

Answer 17

Ho: sample mean 1 = 2 = 3
Ha: sample means aren’t equal

Question 18

What are the 4 requirements for using ANOVAs (sample, LOM, variance, distribution)

Answer 18

• Random, independent samples
• Interval or ratio LOM
• Homogeneity of variance
• Normal distribution

Question 19

How do you calculated degrees of freedom for ANOVAs?

Answer 19

Df = df numerator + df denominator
> Df numerator = # of groups - 1
> Df denominator = total # of subjects - # of groups

Question 20

What is the formula to calculate F-ratio?

Answer 20

F-ratio = (difference b/w groups)/(difference within groups)

Question 21

When an F-ratio is close to 1, do you accept or reject the Ho?

Answer 21

Accept: little difference b/w groups

Question 22

If you don’t have a p value and only an F-ratio, what should you do?

Answer 22

Compare F sample against F critical value table

Question 23

If F sample is > F critical value, is this significant? Do you accept or reject Ho?

Answer 23

Significant, reject

Question 24

What are the 2 requirements for using a repeat measures ANOVA (sample, symmetry)?

Answer 24

• Dependent sample

- Compound Symmetry

Question 25

What are 3 concerns with repeat measures ANOVAs?

Answer 25

• Position/latency effects

- Carryover effects

Question 26

When is the spearman correlation coefficient used?

Answer 26

Ordinal OR not normally distributed

Question 27

When is Pearson’s correlation coefficient used?

Answer 27

Interval/ratio AND normally distributed

Question 28

Correlation coefficients describe what 2 things?

Answer 28

• Direction

- Strength of a linear relationship

Question 29

When a correlation coefficient is positive vs negative, what does this mean in terms of direction?

Answer 29

Positive: variables move in the same direction
Negative: variables move in opposite directions

Question 30

Describe the strength of the relationship:
p/r < 0.3 : ____
0.3 < p/r < 0.5 : ____
0.5 < p/r : ____

Answer 30

weak, moderate, strong

Question 31

How do you calculate the percentage of variance?

Answer 31

r^2 x 100%

Question 32

Percentage of variance describes the % of differences found in the ____ variable can be explained by the ____ variable

Answer 32

dependent, independent

Question 33

Clinically, if r > __, it is significant

Answer 33

0.3

Question 34

If 2 variables have a strong correlation, this means the effect size is ____ and the sample size is ____

Answer 34

large, small

Question 35

What is the purpose of linear regressions?

Answer 35

Make predictions about the future value of DV at a given IV level

Question 36

What is a residual?

Answer 36

Difference b/w actual data points & predicted data points

Question 37

What is the slope of trendline?

Answer 37

How much DV changes per 1-unit change of IV

Question 38

What is the formula for multiple regression?

Answer 38

y = a + b1x1 + b2x2 + e

Question 39

What is the formula for odds ratio (OR)?

Answer 39

odds of outcome occurring/odds of outcome not occurring

Question 40

What is the deference between sensitivity & specificity in terms of screening tests?

Answer 40

Sensitivity: increased true positives, decreased false negatives
Specificity: increased true negatives, decreased false positives

Question 41

What is a positive predictive value (PPV)?

Answer 41

Probability of a true positive

Question 42

What is a negative predictive value (NPV)?

Answer 42

Probability of a true negative

Question 43

When prevalence increases, PPV will ____ meanwhile NPV will ____

Answer 43

increase, decrease

Question 44

What is EFF (efficiency)?

Answer 44

How correct the screening test was vs actual diagnosis