Biostatistics Final Exam

Front 1

What is an Eigenvalue?

Back 1

The standard deviation squared + added...?

Front 2

What is PDF?

Back 2

Probability Distribution Function. When integrated over a set of numbers A, will give prob. of X in A.

Front 3

What is a PMF?

Back 3

Probability Mass Function. Probability that a discrete random variable is equal to some real value.

Front 4

What is a CDF?

Back 4

Cumulative Distribution Function. Probability that a random variable is less than or equal to a certain real number.

Front 5

Describe Central Limits Theorem.

Back 5

Given a large sample size, the distribution of means will be normal. Std error works b/c of Theorem. As we approach infinity, looks normal.

Front 6

What is a random variable?

Back 6

Variable independent from samples what we assign any number or you don't know the number.

Front 7

What is meant by 'power'? Name the 5 components.

Back 7

1-beta. 5 Components: alpha, beta, delta/effect size, n/sample

Front 8

2 Rules of AIC

Back 8

1. Choose lowest value.

2. If within 2 units, use less parameters

Front 9

Covariance vs correlation

Back 9

Correlation is standardized covariance. Covariance is a measure of correlation.

Front 10

What is a linear model?

Back 10

Predicting variable by multiplying parameters.

Front 11

Anova vs Ancova

Back 11

Anova: treating parameters of interest as last variable

Ancova: parameters are NOT multiplied by each other

Front 12

What are the parameters of binomial, poisson, uniform, and normal distributions?

Back 12

Binomial: n (sample), p, q

Poisson: lambda (mean)

Uniform: a (min), b (max)

Normal: Mew (mean), Sigma (s.d)

Front 13

Definition of parameter.

Back 13

Describes population. Truth. You never know parameters true values of full population.

Front 14

Definition of statistic.

Back 14

Estimate is parameters. Ex: slope, correlation, t-score

Front 15

What is an anova test?

Back 15

Only tells if groups are different. Need to do post-hoc test. Tukey HSD most common.

Front 16

T-test equation (hypothesis testing)?

Back 16

[(delta)mean-theta]/std error

Front 17

What correction to use for data?

Back 17

Bonferroni: more conservative

Holm: more liberal

Front 18

What describes shape of distributions: t, F, chi-squared

Back 18

t: df

F: df1, df2

Chi-squared: df

Front 19

What parameter describes chi-squared distribution? Draw it.

Back 19

Degrees of freedom. More df = steeper distribution.

Front 20

Describe F distribution.

Back 20

Parameters: df1, df2. Looks like ch-squared distribution. Approaches infinity, looks normal.

Front 21

Definition of p-value

Back 21

Probability of finding observed results if null were true. How valuable is the data.

Front 22

What are standardized beta values?

Back 22

Slope: 2 parameters measured in different values. Standardized slopes to see which slopes are important.

Front 23

Definitions of mean, median, and mode.

Back 23

Mean: average

Median: middle

Mode: most

Front 24

Definitions of standard deviation and range.

Back 24

Standard deviation: Avg spread of data points around the mean. Also determines how wide your curve is.

Range: difference btwn largest and smallest values

Front 25

Binomial: Parameters, Dis or Con?, Type of data?

Back 25

Parameters: n, p, q

Discrete

Given a probability of something happening, is this gonna happen?

Front 26

Poisson: parameters, Dis or Con?, Type of data?

Back 26

Parameters: lambda (mean)

Discrete

Concerned w/ numbers or counts. Used for rare events.

Front 27

Uniform: parameters, Dis or Con?, Type of data?

Back 27

Parameters: a, b (min, max)

Can be continuous (cdf) or discrete (pmf)

Constant probability.

Front 28

Normal: parameters, dis or con?, Type of data?

Back 28

Parameters: mew, sigma/stdev

Continuous

Data that has a mean and standard deviation. Bell-shaped curve

Front 29

How do you calculate standard error?

Back 29

Stdev or sigma/sqrt(sample size)

Front 30

How do you calculate the 95% Confidence Internal?

Back 30

Mean +/- 1.96*(stdev)

Front 31

How do you calculate the coefficient of variation?

Back 31

(Stdev/mean)*100=%

Front 32

How do you calculate standard deviation?

Back 32

Sqrt((1/N) Epsilon (xi-mew)^2)

Front 33

How do you calculate variation?

Back 33

Average squared deviation from the mean

Front 34

How are t, F, and chi-squared distributions related?

Back 34

Uses df for distribution shape. Both analyze variance.

Front 35

Difference between binomial and poisson glm.

Back 35

Poisson is predicting occurrence based on predictor level. Binomial is predicting events based on predictor level.

Front 36

When to use factorial anova?

Back 36

To compare means of 2 groups

Front 37

When to use random effects?

Back 37

If we think levels we observe in that group too be samples from a larger population

Front 38

When to use go glm?

Back 38

When there's a relationship between variables and accounts for error.