Lecture 9-11

Question 1

An adjust R-squared value is often reported because

Answer 1

It prevents misrepresentation of the results

Question 2

Standardized coefficient determine

Answer 2

The relative strength of the independent variables on the dependent variable

Question 3

Raising the statistical significance cut-off from 0.05 to 0.1 would

Answer 3

Increase the probability of making a type I error

Question 4

Which independent variable in the regression below has the strongest impact on the dependent variable:

Answer 4

Beta coefficients:

Sex: .033

DAYS OF POOR MENTAL HEALTH PAST 30 DAYS -.132

Question 5

The linear equation based on the Ordinary Least-Squares Regression output below is:

Answer 5

Education Years= 13.931 + (0.033Sex) + (-0.132MentalHealth)

Question 6

What is mean centering?

Answer 6

.Creating a whole new variable of (usually) age by substracting the original value from the mean value

Question 7

What is an absolute value?

Answer 7

the magnitude of the value as opposed to directionality or positive/ negative sign

Question 8

What are we trying to achieve when “Comparing Means”

Answer 8

We are trying to compare different means within the sample i.e. various sub-groups of the sample: sexes, ethnicities, union groups

Question 9

What do the “significance tests for comparing means” do?

Answer 9

To decide if differences between the means of sub-groups is generalizable to population

Question 10

What are the types of “significance tests for comparing means”?

Answer 10

T-tests (three kinds)

ANOVA(analysis of Variance) tests

Question 11

Within t-tests, Define the three types of t-tests and their concepts- including one sample, independent sample, paired samples?

Answer 11

one sample: Compare just one unit sample to population
Independent sample: two sub-groups in the sample are compared to each other.
Paired samples: after an intervention (i.e. control experiment), compare the before-after sample means

Question 12

What do Student’s t-test allow us to do?

Answer 12

If an observed difference in sample means also generalizable to population
Cannot tell about strength of correlations, etc.

Question 13

What is a cross-sectional data collection method? What kind of t-test is used?

Answer 13

Collecting data one-time( Member Service Survey open for 3 months). Uses the independent sample t-test

Question 14

What is the longitudinal design? Pros and cons for cross-s and Longitudinal

Answer 14

Longitudinal: collecting data several times over period of time. increases reliability. But more difficult & expensive. Uses the paired samples t-test

Question 15

When do we need to have a null and research hypothesis?

Answer 15

Anytime we do inferential stats and try to draw a conclusion about a population.

Question 16

What is the signif. cut-off for t-test?

Answer 16

0.05

Question 17

What helpful concepts are there when you try to measure or quantify difficult concepts such as happiness, depression and life satisfaction?

Answer 17

Helpful concepts- validity, reliability and measurement error

Question 18

What is validity? An example of validity in a question?

Answer 18

Accuracy of measurement, and reducing measurement error
I.e. when we ask if folks are white, black, Asian, Latinx, Indigenous- are we asking citizenship, language, religion,
genetics, origin of ancestry?

Question 19

How do you get reliability?

Answer 19

test-retest reliability.

Inter-rater reliability

Question 20

What is the relationship between reliability and validity?

Answer 20

a measurement can be reliable but still not valid.

But if it’s not reliable, it’s definitely not valid

Question 21

What is ANOVA? How is it different from independent sample T-tests? why is it more complicated?

Answer 21

Significance test. independent sample T-tests: compare 2 subgroups. ANOVA: compare the variation between 3 or more subgroups. i.e. rural, urban and sub-urban groups. If the signif level is met, then the variation of means can be generalized to the population level

Question 22

What are the values in ANOVA that you need to notice??

Answer 22

F-ratio, Sigfi ratio

Question 23

What does ANOVA NOT calculate?

Answer 23

Since its calculating 3 or more groups, Identify which groups are significantly different from one another

Question 24

What are the similarities between Chi-square and Anova?

Answer 24

Both use a null hypothesis, and operate under the assumption of the null hypothesis

Question 25

What are the significant critiques of T-tests and ANOVA?

Answer 25

They don’t tell the strength Nor the direction of the correlations, unlike OLS Regressions.
They only test bivariate relationships and cannot control other variables.

Question 26

When is it appropriate to use a T-test?

Answer 26

Small sample sizes

Question 27

What test can control different variables?

Answer 27

Multi-variate OLS regressions.

Question 28

Why do we have to use qualifiers in interpretations i.e. there is likely a difference in the average income between different education levels in the population…

Answer 28

Cuz we need to realize that when generalizing to the population, there’s a degree of error involved