Biostatistics

Question 1

Quantitative/Continuous

Answer 1

Variables that can theoretically have values between points (decimal points)

t-test, ANOVA, linear regression

Question 2

Categorical/Discrete

Answer 2

No intermediate values possible (no decimal points)

Chi square, logistic regression (Cohen’s Kappa)

Question 3

Central Tendency

Answer 3

Most frequently used is mean (sensitive to outliers)

Mean, Median, Mode

Question 4

Measures of dispersion (3)

Answer 4

Range (highest to lowest)
Interquartile range (75th percentile minus 25th)
Variance (spread of data around the mean)

Question 5

Dependent

Answer 5

Outcome of interest, in relation to the independent variable

Question 6

Independent

Answer 6

Risk factors or indicators of disease, exposure

Question 7

Parametric

Answer 7

Make an assumption about the underlying distribution

Question 8

Nonparametric

Answer 8

Do not make any assumptions about the distribution, therefore considered robust

Question 9

MED - Minimum Expected Difference

Answer 9

The smallest measured difference between comparison groups that the investigator would like this study to detect

Question 10

P-value

Answer 10

Probability that the finding is because of chance, generally is less than 0.05 the test is statistically significant

Question 11

Power

Answer 11

Ability to find a difference when there is a difference (80%), probability of rejecting the hypothesis

Question 12

Confidence interval

Answer 12

A range that you think will contain the true population parameter that you are measuring
Measure of statistical significance and precision

Question 13

Type 1 error

Answer 13

False discover, when we reject a true null hypothesis

Question 14

Type 2 error

Answer 14

When we fail to reject the null hypothesis that is false

Question 15

t-test

Answer 15

Comparing means of two samples for a statistically meaningful difference

Outcomes have to be continuous

Question 16

Independent sample t-tests

Answer 16

Compares the mean of a sample to some specified value (some value)

Question 17

Two sample t-test

Answer 17

Compares the means of two different independent samples, assumes normality and equality of sample size and variance
(Ex. Compare class 2020 to 2021)

Question 18

Paired t-test

Answer 18

Used for before and after tests or differences between experimental and placebo groups

Question 19

Pearson’s correlation

Answer 19

Measure of strength of linear relationship ‘

r (slope) of 0 may or may not always mean lack of relationship

Positive, negative, no correlation, correlation but no r

Question 20

Cohen’s Kappa

Answer 20

Used to measure observer agreement (inter examiner reliability)

Want value to be close to 1

Between people for consistency

Question 21

Chi square

Answer 21

Compares the observed with the expected

Goodness of fit
Independence and Homogeneity

Question 22

ANOVA

Answer 22

When two or more means are being compared
Similar to the t-test with more factors

Isolates and assesses the contribution of categorical independent variables to variation in the mean of a continuous dependent variable

Question 23

One way ANOVA

Answer 23

There is only one factor that separates the groups into K groups

Question 24

Two way ANOVA

Answer 24

Two categorical independent variables influence a continuous outcome variable

Question 25

Simple linear regression

Answer 25

The outcome is continuous and there is only one continuous predictor (x—>y)

Question 26

Multiple linear regression

Answer 26

Multiple predicts and a continuous outcome (x1,2,3,etc. —>y)

Question 27

Logistic regression

Answer 27

When the outcome is categorical
Used to predict the probability of occurence
One or the other

Question 28

Non-parametric tests

Answer 28

Based on ranks and used when distribution of the data is unknown (cannot make assumptions)

Question 29

Non-parametric test examples

Answer 29

Wilcoxan signed rank test
Wilcox on ran sum test
Kurskal-Wallis test
Spearman Rank correlation