FA 3

Question 1

epidemiology - Mean

Answer 1

Sum of values / total number of values

Question 2

epidemiology - Median

Answer 2

Middle value of a list of data sorted from least to greatest

Question 3

epidemiology - Mode

Answer 3

MC value

Question 4

Measures of central tendency: Most affected by outliers (extreme values)?

Answer 4

mean

Question 5

Least affected by outliers (extreme values)?

Mean mode or median?

Answer 5

mode

Question 6

Measures of dispersion

Answer 6

1. Standard deviation

2. Standard error of the mean

Question 7

Standard deviation (SD or σ)

Answer 7

How much variability exists from the mean in a set of values

Question 8

Standard error of a mean (SEM)

Answer 8

An estimate of how much variability exists between the sample mean and the true population mean

Question 9

Standard deviation - standard error of the mean

Answer 9

SEM=σ/(n riza)

Question 10

Normal distribution (proportion
1σ
2σ
3σ

Answer 10

68%
95%
99.7%

Question 11

Nonnormal distributions

Answer 11

1. Bimodal
2. Positive screw
3. Negative screw

Question 12

Positive skew

Answer 12

Asymmetry with longer tail on right (peak at left)

Mean>median>mode

Question 13

Negative skew

Answer 13

Asymmetry with longer tail on left (peak on right)

Mean is the smaller

Question 14

statistical variance - definition and equation?

Answer 14

Variance is how far a set of numbers are spread out

variance = (standard deviation) in square

Question 15

how to decrease SEM (standard error of the mean)

Answer 15

increases n

Question 16

standard deviation vs precision

Answer 16

increased precision –> decreased standard deviation

Question 17

Alternative H1 vs null (H0) hypothesis

Answer 17

alternative: Hypothesis of some difference or relationship
null: no difference or relationship

Question 18

Outcomes of statistical hypothesis testing

Answer 18

1. Correct results
   a. Null b. Alternative
2. Incorrect results
   a. Type I error (α) Type II error (β)

Question 19

Outcomes of statistical hypothesis testing - correct results explain

Answer 19

1. Stating that there is an effect or difference when one exists (null hypothesis rejected in favor of alternative hypothesis )
2. Stating that there is not an effect or difference when none exists (null hypothesis not rejected)

Question 20

Incorrect result - type I error

Answer 20

Stating that there is an effect or difference when none exists (null hypothesis incorrectly rejected in favor of alternative hypothesis)
FP ERROR

Question 21

type I error….α?

Answer 21

It is the probability of making a type I error

Question 22

type I error…..p?

Answer 22

It is judged against a preset α level of significance (usually 0,05). If p less than 0.05, then there is less than a 5% of chance that the data will show something that is not really there

Question 23

Type II error

Answer 23

Stating that there is not an effect or difference when one exists (null hypothesis is not rejected when it is in fact false)
FN ERROR

Question 24

Type II error …….β?

Answer 24

Β is the probability of making a type II error. Β is related to statistical power (1-β), which is the probability of rejecting the null hypotephesis when it is false

Question 25

Increase statistical power and decrease β by

Answer 25

1. Increase sample size 2. Increase expected effect size 3. Increase precision of measurement

Question 26

confidence interval - definition

Answer 26

range of values in which a specified probability of the means of repeated samples would be expected to fall

Question 27

confidence interval - equation

Answer 27

CI=mean +-Z (SEM)

Question 28

confidence interval often used

Answer 28

95% CI (corresponding to p=0.05)

Question 29

For the 95% CI: | Z?

Answer 29

Z=1.96

Question 30

For the 99% CI: | Z?

Answer 30

Z=2.58

Question 31

95% CI for a mean difference between variables

Answer 31

if it includes 0 then there is no significant difference and Ho is not rejected

Question 32

95% for ODDS ratio or relative risk

Answer 32

IF it includes 1, Ho is not rejected

Question 33

if the CI between 2 groups overlap

Answer 33

usually NO significant difference exists

Question 34

statistical power (1-β)?

Answer 34

the probability of rejecting the null hypotephesis when it is false

Question 35

Common statistical tests

Answer 35

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

Question 36

T - test definition / example

Answer 36

Checks differences between MEANS OF 2 groups | - Comparing the mean blood pressure between men and women

Question 37

ANOVA test - definition and example

Answer 37

Checks differences between means of 3 or more groups | - Comparing the mean blood pressure between members of 3 ethnic groups

Question 38

Chi-square (x^2) test - definition and example

Answer 38

Checks differences between 2 or more PERCENTAGES OR PROPORTIONS of categorical outcomes (NOT MEANS) - Comparing the percentage of members of 3 different ethnic groups who have essential hypertension

Question 39

Meta-analysis?

Answer 39

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

Question 40

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

Answer 40

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 41

t test - types (explain)

Answer 41

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 42

ANOVA - types (explain)

Answer 42

- 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 43

Pearson correlation coefficient (r): range

Answer 43

-1 .....+1

Question 44

the closer the absolute value of r is to 1

Answer 44

the stronger the linear correlation between the 2 values

Question 45

positive vs negative r value -->

Answer 45

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

Question 46

Coefficient of determination

Answer 46

r^2 (value that is usually reported)

Question 47

ROC (receiver operating characteristic) - definition and explanation

Answer 47

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 48

variables - definition

Answer 48

a quantity that changes under different circumstances

Question 49

variables - types and definitions

Answer 49

1. independent variables --> characteristics that an experimenter can change (eg. amount of salt in a diet) 2. dependent variables --> outcomes that reflect the experimental change (blood pressure under different salt regiments)