Flashcards in Statistics II Deck (27):

1

## What does ANOVA stand for?

### Analysis of Variance

2

## What are ANOVA models?

### Statistical models used to analyze the differences between group means and their associated procedures (such as "variation" among and between groups).

3

## What does ANOVA provide in its simplest form?

### ANOVA provides a statistical test of weather or not the means of several groups are equal, and therefore generalizes t-test to more than two groups.

4

## Why should a t-test not be used, if there are more than two groups?

### Doing multiple two-sample t-tests would result in an increased chance of committing a type I error.

5

## What does MANOVA stand for?

### Multivariate Analysis of Variance

6

## When is MANOVA used instead of ANOVA?

### It is used when there are two or more dependent variables.

7

## What questions can MANOVA help to answer?

###
1. Do changes in the independent variable(s) have significant effects on the dependent variables?

2. What are the interactions among the dependent variables?

3. What are the interactions among the independent variables?

8

## What does MANCOVA stand for?

### Multivariate Analysis of Covariance

9

## What does it mean to have a problem with an unbalanced design in an ANOVA test?

### the groups are of different sizes

10

## What is a fixed factor?

###
A factor only occurring in previously fixed values.

e.g. medicine (1, 2, 3)

species (raven, crow)

11

## What is a random factor?

### randomly selected values out of a population of values

12

## When repeating an experiment, what factors would have the same values?

### the fixed factors

13

## What does "Paired Comparison" mean?

###
before/after - design

both measurements must be taken from the same subject

e.g. blood pressure before and after training

behavior in environment A and environment B

14

## What does it mean to have "Repeated Measures"?

###
several effects on each subjects

e.g. several drugs on each subject

15

## What are the advantages of "paired comparison" and "repeated measurement" designs?

###
Variance between individuals can be ignored.

Smaller effects can be measured, which would usually be cancelled out by inter-subject variance.

16

##
Explain the following abbreviation in paired comparisons:

Xi1

Xi2

Di

###
Xi1 ... value for individual i before

Xi2 ... value for individual i after

Di = Xi1 - Xi2 ... difference for individual i

17

## Basic branches of applied statistics:

###
descriptive statistics

inferential statistics (hypothesis testing, confirmatory ... )

exploratory analysis, modeling, data mining

18

## Why is it called inferential statistics?

### Inferences on the whole population are drawn from sample.

19

## Examples of common quantiles?

###
median

upper quartile

lower quartile

deciles

percentiles

20

##
"Bad" data can usually be classified as either

... or

...

###
incomplete or

incorrect

21

## List two potentially serious weaknesses of discarding incomplete records in a data set!

###
1) possibility of selection bias distortions

2) dramatic reduction in the size of data set

22

## Two ways of handling missing data:

###
1) discard incomplete records

2) insert substitute values

23

## One problem with using substituted values for incomplete data:

### Essentially we would be making up data.

24

## An outlier is ...

### ... a value that is very different from the others, or from what is expected.

25

## Difference between experimental and observational studies (and data)?

###
In experimental studies objects are manipulated (e.g. subjects taking different amounts of a drug).

In observational studies data is just recorded (e.g. telephone surveys, data about distant galaxies).

26

## What does it mean if the allocation of subjects to test groups is "double blind"?

### During the experiment neither subject nor experimenter know in which group the subject is in.

27