Chapter 12: Correlational Studies

Question 1

Purpose of a correlational study

Answer 1

to establish that a relationship EXISTS between the 2 variables, and to describe the nature of the relationship. IT DOES NOT MANIPULATE ANYTHING!

Question 2

T/F A correlational study provides an explanation for the relationship

Answer 2

false.

Question 3

how are correlational variables graphed?

Answer 3

via a scatter plot

Question 4

What does the correlational coefficient describe?

Answer 4

describes 3 characteristics:

1) direction of the relationship (positive, negative)
2) format of relationship: linear exponential and inverse,
3) consistency or strength of the relationship– how scattery of the points?

Question 5

Pearson coefficient:

Answer 5

used to describe and measure LINEAR relationships when both variables are NUMERICAL VALUES

Question 6

T/F A pearson coefficient can be used for ordinal data

Answer 6

false. pearson coefficient can only be used when data is numbers

Question 7

monotonic relationship

Answer 7

a relationship that is consistently one-directional, but the magnitude of increasing may not be the same size (ex/ michaelis menton graph)

Question 8

What type of correlation can help describe a monotonic relationshiP?

Answer 8

a spearman coefficient

Question 9

At what point does a correlational research study becoem differential?

Answer 9

when one variable is a non numerical variable and the other is a numerical variable, and when the NON NUMERICAL VARIABLE BECOMES THE VARIABLE THAT SEPARATES THE GROUP

ex/ gender and IQ levels. groups separated by male or female and IQs are measured. male and females are non numerical and thus this study is a differential reserach study.

Question 10

what is a point biserial correlation?

Answer 10

when the non-numerical groups have only 2 categories and they can be assigned a 0 or 1 to determine a correlational coefficient.

Question 11

T/F: the sign of the correlation is meaningless in a point biserial correlation

Answer 11

true, but the strength of the relationship between the non numerical factors can be determined.

Question 12

What can you use as statistical analysis when determining the extent of a correlation between 2 non-numerical variables?

ex/ gender (male and female) vs success (pass or fail)

Answer 12

use a chi square analysis. If there are only 2 categories, you can also perform a phi-coefficient.

Question 13

T/F: the sign of the phi-coefficient for 2 non-numerical variables is meaningful

Answer 13

false. only the strength is meaninful. you cannot determine if it is linear or the sign of the graph because the variables are just asigned numbers 0 or 1.

Question 14

when would you use a phi-coefficient? a point biserial coefficient?

Answer 14

phi: when both variables of study in a correlational design are non numerical

point bi: when one variable of a correlational design is numerical, and the other isnt.

Question 15

what is the coefficient of determination? example?

Answer 15

the r squared value.

measures how much variability in one variable is predictable in its relationship with the other varaible.

ex/ R squared value =0.64. 64% of the difference in GPA can be predicted by the differences in IQ.

Question 16

in order for significance in the correlational value to be valid, the sample population size must be __

Answer 16

large.

Question 17

requirement in order for the significance in the correlational value to be valid

Answer 17

need a large population size

Question 18

in terms of prediction, correlational studies often identify one variable as the ____ and the second variable as the ____. give an example.

Answer 18

in terms of prediction, correlational studies often identify one variable as the PREDICTOR VARIABLE and the second variable as the CRITERION VARIABLE. give an example.

ex/ the correlational relationship between college performance and SAT score can predict how well a student will do in college (criterion variable) based on their SAT score (predictor variable)

Question 19

What statistical process is used to allow correlations to be used for prediction? how is this laid out?

Answer 19

regression is used. Usually the y axis is the criterion, and the x axis is the predictor value.

Question 20

example of an application of a correlational study that is not prediction

Answer 20

to learn about the unknown variable by seeing how it is related to an established variable.

ex/ looking at how genetic factors (known) interact with risk of alzheimers disease (complex and unknown)

Question 21

how is reliability tested in correlational studies?

Answer 21

using the test and retest method

Question 22

how is validity tested in correlational studies?

Answer 22

determined using concurrent validity. do the results of the new correlational test match up with expected results from an old, well established test?

a strong correlation should have high concurrent validity

Question 23

a strong correlation should have ___ ____ validity

Answer 23

a strong correlation should have high concurrent validity

Question 24

Applications of correlational studies?

Answer 24

1) making predictions via statistical regression
2) learning about the unknown
3) evaluating theories.
- theories can generate questions that can be answered via correlational designs. ex/ nature vs nurture. can use a correlational study with twins that were adopted to different parents. you cannot do manipulation though.

Question 25

advantages of correlational design

Answer 25

can identify variables that might suggest further investigation

• high external validity
• can investigate variables that would be unethical to manipulate

Question 26

disadvantages to correlational research design

Answer 26

• low internal validity. no controls
• third variable problem: there is a possibility that a 3rd unidentified variable is controlling the 2 other variables, and is responsible for producing the observed relationship.
• directionality problem. a correlational study does not determine which variable is the cause and which is the effect. it just points out that there is a relationship between two variables.

Question 27

how do you statistically evaluate the relationship of a correlational design that uses more than 2 variables?

Answer 27

ANOVA, and multiple regression statistics to make predictions

ex/ studying IQ, motivation and academic performance. allows researchers to examine the relationship between specific variables while controlling the influence of other confounding variables.
- adding an additional predictor variable into the regression analysis adds to the prediction AFTER the influence of earlier predictors had already been considered.

Question 28

what statistical tests can be done on a correlational study that has more than two groups?

Answer 28

ANOVA

Question 29

what statistical tests can be done on a correlational study with 2 groups?

Answer 29

independent measures T test