Chi-Square Statistics

Question 1

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

Answer 1

Categorical Variables

Question 2

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

Answer 2

Categorical data

Question 3

Take on values that are names or labels

Answer 3

Categorical Variables

Question 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?

Answer 4

Eachother

Question 5

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

Answer 5

continuous data

Question 6

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

Answer 6

Non-normally distributed

Question 7

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

Answer 7

Contingency tables

Question 8

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

Answer 8

1 box

Question 9

What should we always do for contingency tables?

Answer 9

Put totals outside of each row/column

Question 10

The appropriate statistic to use for categorical data

Answer 10

Chi-Square test

Question 11

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

Answer 11

Frequency within each category

Question 12

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

Answer 12

Formulate a model

Question 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

Answer 13

Independent

Question 14

The Chi squared test is written as

Answer 14

χ^2

Question 15

Measure the observed frequencies and compares them to the expected

Answer 15

Chi-squared test

Question 16

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

Answer 16

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

Question 17

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

Answer 17

Reject the null hypothesis

Question 18

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

Answer 18

Can not reject null hypothesis

Question 19

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

Answer 19

Fisher Exact Test

Question 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

Answer 20

Independent of eachother

Question 21

The study of disease occurence in human populations

Answer 21

Epidemiology

Question 22

Epidemiology also uses

Answer 22

Contingency tables

Question 23

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

Answer 23

Cohort studies

Question 24

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

-like i the bone mineral example

Answer 24

Case-control studies

Question 25

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

Answer 25

Case-control study

Question 26

For a case-control study, we use the

Answer 26

Odds ratio (OR)

Question 27

When using the odds ratio, OR = 1 means

Answer 27

No difference in odds of exposure

Question 28

When using the odds ratio, OR > 1 means

Answer 28

The odds of getting the disease are increased w/ exposure

Question 29

When using the odds ratio, OR less than one

Answer 29

The odds of getting the disease decrease w/ exposure

Question 30

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

Answer 30

No effect of the exposure

Question 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.)

Answer 31

One way ANOVA

Question 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.)

Answer 32

Multiple Measures ANOVA