Chapter 5

Question 1

A statistical association between variables

Answer 1

correlation

Question 1

A statistical association between variables

Answer 1

correlation

Question 2

Examining potential associations between variables. This is the research into statistical relations and the relations might be a coincidence.

Answer 2

correlational research

Question 3

What is the difference between correlational research and causational research?

Answer 3

1. measure variable x in correlational and manipulate in causational research
2. Must eliminate confounding variables in causational research

Question 4

What is the same between correlational research and causational research?

Answer 4

Attempting to reduce confounding variables

Question 5

Higher scores of one variable increase with the other variable

Answer 5

positive corrolation

Question 6

Higher scores of one variable increase as the other variable decreases

Answer 6

negative corrolation

Question 7

A statistical measure that measures the direction and strength of the linear relation between two variables that have been measured on an interval or ratio scale

Answer 7

pearson’s r

Question 8

How to understand pearson’s r

Answer 8

the closer it is to -1.00 or 1.00, the stronger the linear relationship is

Question 9

A statistic used to measure the relation between two quantitative variables when variables are measured on an ordinal scale

Answer 9

spearman’s rho

Question 10

two things that might effect spearman’s rho

Answer 10

1. the way higher or lower are numerically coded can change the results being a negative number to a positive number
2. the wording used can change the results

Question 11

A graph in which data point portray the intersection of X and Y

Answer 11

scatter plot

Question 12

Why use a scatter plot

Answer 12

1. They can show non linear relations
2. provide a visual representation of the strength of corrolations

Question 13

Pearson’s r of .10 to .29

Answer 13

small association

Question 14

Pearson’s r of .30 to .49

Answer 14

moderate association

Question 15

Pearson’s r of . 50 to 1.00

Answer 15

strong association

Question 16

What happens when pearson’s r is squared

Answer 16

shows the variation in the results

Question 17

Three key criteria used in drawing causal inferences

Answer 17

1. Covariation of X and Y. As X changes, Y changes
2. Temporal order. Changes in X occur before changes in Y
3. Absence of plausible alternative explanations

Question 18

Why can a correlational study not draw conclusions?

Answer 18

Because X variable is not manipulated, temporal order cannot be established

Question 19

The problem of ambiguity about whether X did cause Y

Answer 19

Bidirectionality problem

Question 20

The problem is that there might be another variable between X and Y

Answer 20

variable problem

Question 21

A correlation between variable X and variable Y is computed while statistically controlling for their individual correlations with a third variable Z

Answer 21

Partial Correlation

Question 22

Each person participates on one occasion, and all variables are measured at that time

Answer 22

cross-sectional research design

Question 23

Data are gathered on the same individuals or groups in two or more occasions

Answer 23

longitudinal research design

Question 24

a type of longitudinal design where variable X is measured at an earlier point then variable Y

Answer 24

prosepective design

Question 25

Three steps of cross-lagged panel design

Answer 25

1. Measure X and Y 2. Meausre X and Y again 3. examine the pattern of correlations of all variables

Question 26

Three steps of cross-lagged panel design

Answer 26

1. Measure X and Y 2. Meausre X and Y again 3. examine the pattern of correlations of all variables

Question 27

What are the main issues with correlational research that does not allow for causational conclusions.

Answer 27

The lack of control over confounding variables and not manipulating the independant variable

Question 28

A predictor that explores the quantitative, linear relation between two variables. It is often used to predict scores of one variable based on another.

Answer 28

Regression analysis

Question 29

The varible that we are trying to eliminate or predict

Answer 29

criterion variable

Question 30

The variable whose scores are used to estimate the criterion variable

Answer 30

predictor variable

Question 31

A line that is the visual representation of the average on a scatter plot

Answer 31

regression line

Question 32

Predicting the linear relations between multiple variables

Answer 32

multiple regression

Question 33

key concept of multiple regression

Answer 33

each new predictor variable must enhanse our ability to predict the criterion variable

Question 34

Uses for correlational research

Answer 34

1. Standardized tests 2. Measures used for mental disorders 3. Test validation 4. Experiments that cannot manipulate the independent variable 5. Hypothesis testing to find new theories

Question 34

Uses for correlational research

Answer 34

1. Standardized tests 2. Measures used for mental disorders 3. Test validation 4. Experiments that cannot manipulate the independent variable 5. Hypothesis testing to find new theories

Question 35

Occurs when the range of scores obtained have been limited

Answer 35

range restriction

Question 36

When scores cluster around the maximum

Answer 36

ceiling effect

Question 37

What statistical measurement to use in associations involving categorical variables

Answer 37

pearson's r or spearman's rho

Question 38

When can you not use pearson's r

Answer 38

with non linear relationships