L3 - Inferential Analysis

Question 1

What is operationalization?

Answer 1

Question 2

What is content validity?

Answer 2

Is the measure a good implementation of the theoretical construct?

–> Content validity

Question 3

Confounding variable

Answer 3

A variable that might be correlated with the IV and might actually be the influence on the DV

Question 4

Moderator

Answer 4

Might affect the relationship between IV and DV

Question 5

Mediator

Answer 5

Establishes the relationship between the IV and the DV

Question 6

Difference between experimental and correlational research

Answer 6

Experimental: IV is explicitly manipulated
Correlational: IV and DV vary naturally in sample

Question 7

What is within-subjects design

Answer 7

Same person is presented with several levels of the manipulated variable

Question 8

Between-subjects design

Answer 8

Different people are presented the different levels of the manipulated variable

Question 9

Is a universal hypothesis verifiable?

Answer 9

If you only have a sample from population then no.

, “All employées in tech companies are short-sighted.“

Question 10

Is an existential hypothesis verifiable with a sample from the population?

Answer 10

Yes. But not falsifiable.

“There are employées in tech companies that are short-sighted.“)

Question 11

Can proportions or trends be verified or falsified with a sample from the population?

Answer 11

No both not.
“55% of employées in tech companies are short-sighted.”

Question 12

Can we make a decision on whether to accept or reject an hypothesis based on statistical inference?

Answer 12

yes

Question 13

What is Fisherian approach

Answer 13

set up probability distribution under H0

Question 14

What is the Neyman-Pearson approach?

Answer 14

set up H1 and H2

Question 15

What is the effect size?

Answer 15

• Difference between H1 and H2

Question 16

What is type 1 error?

Answer 16

If the state of the world H1 true but you accept H2

Question 17

What is type 2 error

Answer 17

If the state of the world is H2 but you accept H1.

Question 18

What is power?

Answer 18

1-ß
When H2 is state of the world and you accept H2

Question 19

What is the p-value

Answer 19

probability of observed test statistic under H0

Question 20

Is the p-value a measure of the evidence of the hypothesis

Answer 20

no

Question 21

Q6: Imagine you ran a statistical inference test and obtained a p-value of p = .01. Which of the following statements correctly describes your situation (multiple responses possible)

Answer 21

You have found the probability that if the null hypothesis is true, you would get results as extreme (or more extreme) as what you have observed.

Question 22

Is the effect size dependent on the p-value?

Answer 22

No

Question 23

What is a small effect size?

Answer 23

.2

Question 24

What is a large effect size?

Answer 24

.8

Question 25

Which test to compare means of two independent groups?

Answer 25

Independent-samples t-test

Question 26

Which test for comparing the means of two related sets of observations?

Answer 26

Dependent samples t-test

Example: Happiness of a group of people before and after an election
(i.e., each person measured twice)

Question 27

Which test for comparing the mean of one group against a single value?

Answer 27

one sample t-test

Example: Protein content of sample of packages of an energy bar to see whether they contain 20g of protein (as indicated on the package)

Question 28

Computing the expected frequency under H0 of two nominal variables

Answer 28

Question 29

What is Chi-squared used for?

Answer 29

Analyzing the association of two nominal variables. Chi-squared is the normalized different between observed and expected frequencies

Question 30

What does Cramer’s V measure

Answer 30

effect size between two nominal variables

Question 31

With a larger sample size, the actual values in the population are better reflected; variability around the true value becomes smaller.

What is this called?

Answer 31

Central Limit Theorem

Question 32

Reminder: What is the power?

Answer 32

Question 33

Does the power vary for different effect sizes?

Answer 33

Yes. Larger effect size, larger power

Question 34

Does the power depend on the sample size?

Answer 34

Yes, because larger samples are more peaked. The larger the sample, the higher the power.

Question 35

What is the a priori power analysis about?

Answer 35

How large should the sample size be to have a good change to detect the hypothesized effect?