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Flashcards in Chi-Square Statistics Deck (32):
1

Data sets that are not contiguous. For example: Dead or alive, head injury or no head injury, cancer or no cancer, etc.

Categorical Variables

2

There is no mean,median, mode, or normal distribution for

Categorical data

3

Take on values that are names or labels

Categorical Variables

4

Different categorical variables can be associated with

-Ex: Is there a difference between college students and medical students in the number of hours of sleep per week?

Eachother

5

Categories may be inherent in the data or created by the researchers from

continuous data

6

We may want to change the data into categories if the categories are more clinically meaningful, or if the data are

Non-normally distributed

7

What is the conventional data presentation for the associations between categorical variables?

Contingency tables

8

In a contingency table, all data is independent, meaning that each person fits into only

1 box

9

What should we always do for contingency tables?

Put totals outside of each row/column

10

The appropriate statistic to use for categorical data

Chi-Square test

11

In the Chi-square test, we first want to establish categories and the determine the

Frequency within each category

12

Once we know the frequency within each category, we want to

Formulate a model

13

The last thing we want to do in our Chi square test is compare the normal to the expected to see if the categories are

Independent

14

The Chi squared test is written as

χ^2

15

Measure the observed frequencies and compares them to the expected

Chi-squared test

16

How do we calculate the expected values for each box on the contingency table?

Expected value = (row total x column total) / grand total

17

For the chi-squared test, if our calculated value of X^2 is GREATER than the critical value, we

Reject the null hypothesis

18

For the chi-squared test, if our calculated value of X^2 is LESS than the critical value, we

Can not reject null hypothesis

19

The Chi-squared test is not valid for a 2x2 contingency table with very small samples. In this case, we use a

Fisher Exact Test

20

In Chi-squared tests, we make the assumptions that the data are frequency data, there is an adequate sample size, and the measures are

Independent of eachother

21

The study of disease occurence in human populations

Epidemiology

22

Epidemiology also uses

Contingency tables

23

Follow two groups of people, some who are exposed to a factor

Cohort studies

24

Look at people with and without the disease and determine whether or not they were exposed

-like i the bone mineral example

Case-control studies

25

Measures the odds of getting a disease, given an exposure, and compares that to the odds of getting the disease without it

Case-control study

26

For a case-control study, we use the

Odds ratio (OR)

27

When using the odds ratio, OR = 1 means

No difference in odds of exposure

28

When using the odds ratio, OR > 1 means

The odds of getting the disease are increased w/ exposure

29

When using the odds ratio, OR less than one

The odds of getting the disease decrease w/ exposure

30

If the 95% confidence interval contains 1, than there is

No effect of the exposure

31

Used when data is normally distributed, there are more than 2 groups, and each person can only fall into one of the groups (I.e. Married, divorced, single, etc.)

One way ANOVA

32

Used when the data is normally distributed, and you want to do multiple tests on a single group (I.e. Taking blood pressure measurements at various times of the day.)

Multiple Measures ANOVA

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