Statistics

Question 1

Sensitivity definition

Answer 1

true positive rate proportion of all people with the disease that test (+) for disease when disease is present values approaching 100% desirable for ruling out disease

Question 2

Sensitivity equation

Answer 2

= TP / (TP + FN) = 1 - (false negative rate)

Question 3

specificity definition

Answer 3

true negative rate proportion of people without the disease who test (-) values approaching 100% desirable for ruling in disease

Question 4

specificity equation

Answer 4

= TN / (FP + TN) = 1 - (false positie rate)

Question 5

positive predictive value definition

Answer 5

proportion of positive test results that are true positives

Question 6

positive predictive value equation

Answer 6

= TP / (TP + FP)

Question 7

negative predictive value definition

Answer 7

proportion of negative test results that are true negative

Question 8

negative predictive value equation

Answer 8

= TN / (TN+ FN)

Question 9

Incidence looks at the number of _____ cases in a SPECIFIC period of time

Answer 9

new cases

Question 10

prevalence looks at _____ cases in a SPECIFIC period of time

Answer 10

all existing cases

Question 11

incidence equation

Answer 11

incidence rate = (# of new cases in a specific time period)/ (population at risk during same time period)

Question 12

prevalence equation

Answer 12

prevalence = (# of existing cases) / (population at risk) approximately equal to (incidence rate) X (average disease duration)

Question 13

Risk / disease ratio table

Answer 13

Disease

+ -

risk factor + a b

                           -        c                  d

Question 14

odds ratio

• study used in
• definition

Answer 14

case control studies

odds that the group with the disease (cases) was exposed to a risk factor (a/c) **divided by **the odds that the group without the disease (controls) was exposed (b/d)

Question 15

odds ratio equation

Answer 15

= (a/c) / (b/d)

= ad/ bc

Question 16

relative risk

• study used in
• definition

Answer 16

cohort study

risk of developing disease in exposed group **divided by ** risk in the unexposed group

Question 17

relative risk equation

Answer 17

= (a/(a+b)) / (c/(c+d))

Question 18

attributable risk definition

Answer 18

difference in risk between exposed and unexposed groups

or

the proportion of disease occurence that are attributable to the exposure

Question 19

attributable risk equation

Answer 19

= (a / (a+b)) - (c/(c+d))

Question 20

absolute risk reduction equation

Answer 20

ARR = (control event risk) - (experiment event rate)

Question 21

number needed to treat

• definition
• equation

Answer 21

number of patients who need to be treated for 1 patient to benefit

= 1/ ARR

Question 22

number needed to harm

• definition
• equation

Answer 22

number of patients who need to be exposed to a risk factor for 1 patient to be unharmed

= 1/ attributable risk

Question 23

Standard error of Mean (SEM) =

Answer 23

(standard deviation) / (square root of sample size)

as sample size increases, standard error of mean decreases

Question 24

normal distrubtion

Answer 24

bell shaped curve (gaussian)

mean = median = mode

Question 25

positive skew vs. negative skew

Answer 25

positive: mean \> median \> mode asymmetry with longer tail on right negative: mode \> median \> mean asymmetry with longer tail on left

Question 26

Null hypothesis (Ho)..... hypothesis of no difference Alternative (H1)... hypotheis of some difference chart

Answer 26

reality H1 Ho study result H1 power (1 - beta) alpha Ho beta correct

Question 27

Type I error (alpha)

Answer 27

accept alternative and reject null hypothesis states that there is an effect or difference when none exists if P \< .05 -there is a 5% chance that the data will show something that is not really there

Question 28

type II error (beta)

Answer 28

accept null... reject alternative hypothesis stating that there is **not** an effect or difference when one exists false negative

Question 29

power (1- beta)

Answer 29

probability of rejecting null hypothesis when it is in fact false or the likelihood of finding a difference if one in fact exists

Question 30

Confidence interval equation

Answer 30

CI = [mean - Z(SEM)] to [mean + Z(SEM)] SEM = standard error of mean Z = Z-score for the 95% CI: z = 1.96 for the 99% CI: z = 2.58

Question 31

if 95% CI for a mean difference between two variables **includes 0**, then there is _____ difference and Ho is \_\_\_\_\_

Answer 31

no significant difference Ho is not rejected

Question 32

if the 95% CI for odds ratio or relative risk **includes 1**, Ho is \_\_\_\_

Answer 32

not rejected

Question 33

If the CIs between 2 groups **do not** overlap, then \_\_\_\_ if the CIs between two groups **do** overlap, then \_\_\_\_

Answer 33

**do not**: significant difference exists **do**: usually not significant difference exists

Question 34

test that checks for the difference between the **means** of **two **groups

Answer 34

T-test

Question 35

test that checks difference between **means** of **3 or more** groups

Answer 35

ANOVA | (analysis of variance)

Question 36

test checks difference between **two or more percentages** **or proportions** of **categorical** outcomes (not mean values)

Answer 36

chi-square (X²) compares percentages or proportions

Question 37

Parson's correlation coefficient (r)

Answer 37

r is always between -1 and +1 closer the absolute value of r is to 1: the stronger the linear correlation between two variables coefficient of determination = r²