Exam 2

Question 1

t distribution

Answer 1

• we use a sample standard deviation s instead of population standard deviation
• used when you don’t know population sd
• similar to normal but “thicker tails
• shape depends on sample size: df = n-1
• the bigger the sample size, the closer to normal

Question 2

95% Confidence interval

Answer 2

x - tcrit (s/sqrtn) < u < x + tcrit (s/sqrtn)

Question 3

conditions/assumptions of t test

Answer 3

• random sample
• observations should be independent of each other
• population should be normal or n >25

Question 4

steps to hypothesis testing

Answer 4

1. hypothesize: state null and alternative
2. prepare: set sig level at 0.05, select test, check assumptions, find critical value
3. compare: compute test statistic and compare to critical value or example 95% CI
4. interpret

Question 5

p-value

Answer 5

the probability of observing a t-statistic at least as extreme as the one you calculated, assuming your hypothesis is true

Question 6

one sample t test

Answer 6

compares 1 sample mean to a comparison value of interest

Question 7

independent samples t-test

Answer 7

-compares samples from two different groups to see if the means are significantly different

Question 8

paired (or dependent-samples) t-test

Answer 8

-comparing one sample to another related sample to see if there are differences within pairs

Question 9

one-tailed test

Answer 9

non-directional

Question 10

two-tailed

Answer 10

directional

Question 11

Chi-Squared Goodness of Fit

Answer 11

-test if one categorical variable matches the expected distribution

Question 12

test of independence

Answer 12

-test whether there is an association between two categorical variables

Question 13

conditions/assumptions of chi-squared

Answer 13

• random sample, independent observations
• sample size: at least 1 of each expected count
• 80% of expected counts should be >5

Question 14

chi-square

Answer 14

sum (((observed-expected)^2)/expected)

Question 15

expected count (for chi squared)

Answer 15

(row total x column total)/grand total

Question 16

df for chi-square of independence

Answer 16

df = (rows-1)(columns-1)

Question 17

df for chi-squared goodness of fit

Answer 17

df = #groups - 1

Question 18

odds ratio

Answer 18

• odds of X happening in the presence of Y divided by the odds of x happening without the presence of Y
• (p1/(1-p1))/(p2/(1-p2))

Question 19

relative risk

Answer 19

• compare the probability of x happening in the presence of y and not in the presence of y
• (a/(a+b))/(c/(c+d))

Question 20

when the disease is rare

Answer 20

OR = RR

Question 21

when the disease is common

Answer 21

OR&raquo_space; RR

Question 22

options for violation of assumptions for OR or RR

Answer 22

• ignore the violation
• transform the day to avoid violations: apply a function y= f(y); neg skewed? try power transforms
• use a nonparametric method
• use a permutation test

Question 23

detecting violations

Answer 23

• when sample sizes are very small (n<15) it is very difficult
• use nonparametric test

Question 24

Wilcox-mann-whitney U test

Answer 24

• non-parametric alternative to independent samples t-test
• compares distributions of two groups
• hypothesize, rank all data from least to greater, take sum of ranks for R1

Question 25

U statistic

Answer 25

U1 = n1n2 + (ni(ni+1))/2 - R1
U2 = n1n2 - U1
U = Max (U1, U2)
-if U > Ucrit, reject null hypothesis