Lecture 5 Flashcards Preview

Stats Midterm > Lecture 5 > Flashcards

Flashcards in Lecture 5 Deck (20)
Loading flashcards...
1

What type of research is described when we analyze data that was collected through self-report surveys or interviews?

Survey research

2

Most correlational research is what?

Survey/self-report

3

What is it called when survey participants don't answer questions truthfully?

Response sets

4

How do you control for response sets?

Anonymous data collection
Lie scales
Negative wording/reverse coding

5

What are the percentages of surveys/questionnaires that are successfully completed and returned?

Response Rates

6

In response rates what is considered good?

60%

7

In response rates what is considered inadequate?

Less than 50%

8

Low response rates suggest what?

Sample isn't representative of all persons in that population

9

What are follow ups of non respondents that's used to increase initial response rate?

Second wave contacts

10

What are a few pros of interviews?

probing
high response rates
explanations given

11

What are a few cons of interviews?

expensive
takes longer
train people

12

What are a few pros of written surveys?

large samples
quick and easy

13

What are a few cons of written surveys?

no probing
less serious responses
limitations in generalizing

14

What does linear regression allow us to do?

Predict one variable from another

15

What is the equation for linear regression?

y=bX+a
y=predicted score( Dependent variable)
b=slope
X=predictor variable score (Independent Variable)
a=Y intercept

16

When doing a scatterplot for regression where should X and Y be?

Predicted on Y (Dependent variable)
Predictor on X (Independent variable)

17

What is the number that SPSS prints when it calculates a regression equation?

Standard Error of Estimate

18

The standard error of estimate indicates what?

how different the Y scores we predict with the equation will be from the person's actual score for Y.

19

The higher the r of r2 the better the what?

prediction will be and lower standard error of estimate will be.

20

What are the assumptions in linear regression?

Linearity
Normality
Homoscedastivity