Lecture 9

Question 1

What are the three types of t-tests?

Answer 1

• independent t-test
• matched t-test
• one sample t-test

Question 2

What is the purpose of t-tests?

Answer 2

used to compare means between groups (can be independent or dependent)

Question 3

What is the difference between a category and a variable?

Answer 3

categories are NOT variables, the subgroups OF a variable are the categories, variable is the common umbrella of the categories

Question 4

When would a t-test NOT be ran?

Answer 4

• when comparing more than 2 groups

Question 5

What will occur if a t-test is used for more than 2 variables?

Answer 5

Type I error will increase if t-test is used for more than two variables- by chance of running multiple comparison test, groups will have a significant outcome even if it’s not

Question 6

What type of variable is only ever used in ANOVA (for this course)?

Answer 6

independent variables

Question 7

What are the requirements of an ANOVA test?

Answer 7

• populations are approximately normal
• POP variances are equal
• sample values are interval or ratio
• samples are reorganized in only ONE way
• hypothesis is regarding population

Question 8

What can alternate hypotheses NOT be in ANOVA?

Answer 8

cannot be an unequality statement- must be “at least one group is different…”

Question 9

What is the variance check equation?

Answer 9

largest variance / smallest variance = value LESS than 9

Question 10

What is the Sum of Squares Between/Model Equation?

Answer 10

SS between = sum of
[(mean of group - mean of ALL groups)^2] * # individuals PER group

Question 11

What does the SS between value represent?

Answer 11

the variance that CAN be explained by the treatment/factor variable (a higher value is desired- means the treatment is beneficial)

Question 12

What is the Sum of Squares Error Equation?

Answer 12

SS error = sum of (sum of (individual’s score - GROUP mean)^2)

Question 13

What does the SS error value represent?

Answer 13

the variance that CANNOT be explained by the treatment/factor (lower value preferred)

Question 14

What is the SS total equation?

Answer 14

SS between + SS error

Question 15

What is the overall df equation?

Answer 15

df overall = n - 1, n: # participants across ALL groups

Question 16

What is the between df equation?

Answer 16

df between = k - 1, k:# GROUPS being ocmpared

Question 17

What is the error df equation?

Answer 17

df error = n - k

Question 18

What is the mean squares equation for between and error?

Answer 18

SS between or error / df between or error

Question 19

What does the mean squares value represent?

Answer 19

the average deviation of individual values from their respective mean (average amount of variation)

Question 20

What is the F-statistic (ratio) equation?

Answer 20

F-Stat = mean square between / mean square error

Question 21

Which value is the signal and which is the noise?

Answer 21

between = signal
error = noise

Question 22

What does an F-ratio near 1 indicate?

Answer 22

almost equal signal to noise ratio (treatment makes no difference)

Question 23

When is the null rejected?

Answer 23

What the p-value is > 0.05, at LEAST one group is different from the others (don’t know which one)

Question 24

What is the relationship between power and beta?

Answer 24

power = 1 - beta
are inversely related

Question 25

What are the 3 parameters used to determine sample size?

Answer 25

- beta value - alpha value - effect size (ES)

Question 26

When power increases, what happens to alpha?

Answer 26

alpha also increases

Question 27

When power increases, what happens to beta?

Answer 27

beta decreases

Question 28

What is the relationship between power, effect and sample size?

Answer 28

the higher the power, the larger the effect and sample size

Question 29

For one sample, continuous data, what is the ES equation?

Answer 29

ES = |mu 1 - mu 0|/ sigma

Question 30

For one sample, continuous data, what is the sample size equation?

Answer 30

n = (z 1-a/2 + z 1-b / ES) ^2

Question 31

How is beta values found?

Answer 31

based on the power percentage, the Z-table is used in reverse to find a value near the power % and the coordinate is the z 1-b value

Question 32

How is alpha / 2 found?

Answer 32

same as beta

Question 33

For one sample, dichotomous outcome, what is the ES equation?

Answer 33

ES = |p1 - p0| / root (p0 *(1 - p0)

Question 34

For one sample, dichotomous outcome, what is the n equation?

Answer 34

n = same as one sample, continuous outcome

Question 35

For two independent samples, continuous outcome, what is the ES equation?

Answer 35

ES = |mu 1 - mu 2| / sigma

Question 36

For two independent samples, continuous outcome, what is the n equation?

Answer 36

n = 2 (z 1-a/2 + z 1-b/ES)^2 - value obtained is sample size PER independent sample

Question 37

What is the n equation when factoring in attirition rate?

Answer 37

N (number to enroll) * % retained = desired sample size % retained = 1 - attrition rate

Question 38

For matched samples, continuous outcome, what is the ES equation?

Answer 38

ES = mu d / sigma d

Question 39

For matched samples, continuous outcome, what is the n equation?

Answer 39

n = same as other n equation, NOT 2x

Question 40

For two independent samples, dichotomous outcomes, what is the ES equation?

Answer 40

ES = |p1 - p2| / root (p*(1-p) - p1: deisred proportion $ (20% OF the X% sample) - p2: the current proportion % - p: pooled proportion (desired p + current p/ 2, the average

Question 41

For two independet samples, dichotomous outcomes, what is the n equation?

Answer 41

n = 2 (z 1-a/2 + z 1-b / ES) ^2 - value is # people needed PER group