Probability and Statistical significance

Question 1

What are 2 ways studies can screw up?

Answer 1

random error and bias/systematic error

Question 2

Does random error bias a study?

Answer 2

No. It may be wrong, but the study isn’t biased.

Question 3

How do you deal with random error?

Answer 3

Statistical Inference.

Question 4

T/F: a study who’s results are deemed statistically significant is also clinically relevant/meaningful

Answer 4

FALSE. You can have small measures of association be statistically significant, that are too small to matter.

Question 5

What are 2 values that we can use to estimate how much random variation there is in our study?

Answer 5

confidence intervals and P values.

Question 6

____ samples have ____ CIs, and _____ samples have ____ CIs

A. large samples, large CIs; small samples small CIs
B. small samples, large CIs, large samples, large CIs
C. small samples, large CIs, large samples, small CIs

Answer 6

C. small samples, large CIs, large samples, small CIs.

Question 7

What does the CI need to include or not in order for the odds ratio to be statistically significant?

Answer 7

The CI for the OR should not include 1, for the OR to be statistically significant.

Same rules apply to relative risk and prevalence ratios.

Question 8

What are P-values?

Answer 8

they essentially tell you the same thing as a CI, but CIs also tell you more. P-values only estimate whether a measured association was likely to have been caused by chance.

-no info about where true value is, or size of sample.

Question 9

What does the P-value need to be, for it to be statistically significant?

Answer 9

It needs to be less than 0.05

Question 10

T/F: you can prove that something is true.

Answer 10

False. You can only prove that something is not true.

Question 11

What is the null hypothesis?

Answer 11

The hypothesis of no association…there is no association between exposure and dz

Question 12

What is the alternative hypothesis?

Answer 12

That there is an association between exposure and dz.

Question 13

If your P-value is less than 0.05, do you accept or reject the null hypothesis?

Answer 13

reject it. There is an association, so you accept the alternative hypothesis.

Question 14

What is type I error?

Answer 14

False positive. You reject the null hypothesis when it is not false (so you are saying there is an association when there isn’t)

Question 15

What is a Type II error?

Answer 15

False negative. You are failing to reject the null hypothesis, when it is actually false.

Question 16

Which of the following is very sensitive to extreme values?

A. median
B. Mean
C. mode

Answer 16

B. Mean

Question 17

What is dispersion?

Answer 17

Measures how closely the values are gathered around the center of distribution

Question 18

What are 2 measures of dispersion?

Answer 18

range and standard deviation

Question 19

When are Chi-squared tests used?

Answer 19

For categorical data. They measure difference in proportions.

Question 20

When are student’s t-test used?

Answer 20

when looking at continuous data. Looks at the difference in means

Question 21

If your independent (explanatory) variable is categorical, and our outcome variable is categorical, what test should you use?

Answer 21

Chi-squared

Question 22

If your independent (explanatory) variable is categorical, and our outcome variable is continuous, what test should you use?

Answer 22

Student’s t-test.

Question 23

If your independent (explanatory) variable is continuous, and our outcome variable is continuous, what test should you use?

Answer 23

correlation

Question 24

What does the correlation coefficient tell us?

Answer 24

it indicaes the strength and direction of a linear relationship between 2 continuous relationships. (strong = >.80)