Common Statistical Test and r

Question 1

T - test example

Answer 1

Comparing the mean blood pressure between men and women

Question 2

Common statistical tests

Answer 2

1. t-test
2. ANOVA
3. Chi-square (x^2)

Question 3

ANOVA test - action

Answer 3

Checks differences between means of 3 or more groups

Question 4

ANOVA test example

Answer 4

Comparing the mean blood pressure between members of 3 ethnic groups

Question 5

Chi-square (x^2) test

Answer 5

Checks differences between 2 or more PERCENTAGES OR PROPORTIONS od caregorcal outcomes

Question 6

Chi-square (x^2) example

Answer 6

Comparing the percentage of members of 3 different ethnic groups who have essential hypertension

Question 7

T test

Answer 7

Checks differences between MEANS OF 2 groups

Question 8

Pearson correlation coefficient (r): range

Answer 8

-1 …..+1

Question 9

the closer the absolute value of r is to 1

Answer 9

the stronger the linear correlation between the 2 values

Question 10

positive r value –>

Answer 10

positive correlation: as one variable increases, the other variable increases

Question 11

negative r value –>

Answer 11

negative correlation:as one variable increases, the other variable decreases

Question 12

Coefficient of determination

Answer 12

r^2 (value that is usually reported)

Question 13

Pearson correlation coefficient - symbol

Answer 13

r

Question 14

epidemiology - r - means?

Answer 14

Pearson correlation coefficient

Question 15

ANOVA meaning

Answer 15

Analysis of Variance

Question 16

t-test vs ANOVA vs CHI-square according to action

Answer 16

t-test –> checks difference between means of 2 groups
ANOVA –> Checks differences between means of 3 or more groups
CHI-square –> Checks differences between 2 or more percentages or proportions of categorical outcomes (not mean values)

Question 17

ROC

Answer 17

receiver operating characteristic

Question 18

ROC (receiver operating characteristic) - definition and explanation

Answer 18

is a graphic representation between sensitivity (y axis) and 1-specificity (FP rate) (x axis) for a diagnostic test
explanation –> the closer the curve is to the diagonia, the less discriminating ability of the test. The closer the curve to the y axis, the better discriminating ability of the test

Question 19

variables - definition

Answer 19

a quantity that changes under different circumstances

Question 20

variables - types

Answer 20

1. independent variables

2. dependent variables

Question 21

independent variables?

Answer 21

characteristics that an experimenter can change (eg. amount of salt in a diet

Question 22

dependent variables?

Answer 22

outcomes that reflext the experimental change (blood pressure under different salt regiments)

Question 23

t test - types (explain)

Answer 23

independent (nonpaired) –>2 different groups of persons are sampled on one occasion (eg. one group with the drug A, and one group with the drug B)
dependent (paired) –> The same persons are sampled on 2 occasions (before and after the treatment)

Question 24

ANOVA - types (explain)

Answer 24

• one way analysis –> 1 variable (eg. weight loss mean in 3 different programs)
• 2 way analysis –> 2 variables (eg. weight loss mean in 3 different programs and men vs women)

Question 25

Meta-analysis?

Answer 25

a statistical procedure that integrates the results of several independent studies considered to be combinable