Ch. 6 Correlation

1. Introduction

1. First step in determining cause-effect

2. Evaluation of tests



2. Scatter plot: defined as the graph of paired X and Y values.

a. How to
STUDENT STATS GRADE ANXIETY SCORE
1 7 3
2 5 4
3 2 9
4 6 4
5 10 1


















b. Linear Relationship vs. Curvilinear Relationship

3. Equation of a straight line:










4. Types of relationships

a. Positive





b. Negative



c. Perfect



d. Imperfect








5. Correlation/Correlation coefficient

A. Magnitude, Direction of correlation coefficient







B. Link between scatter plot and correlation coefficient



















3.Pearson r

A. Definitions 1: Pearson r measures the extent to which paired scores occupy the same or opposite position within their own distributions
TEST MEAN STANDARD DEVIATION RAW SCORE
Assignment 15 2.5 16(80%)
Test 36 6 48(80%)












B. Qualities

1. Independent of scale units, number of subjects, differences in variability









4. Calculation of Pearson r















5. Pearson r and explained variability























A. coefficient of determination










6. Other correlation coefficients

A. Spearman Rho















Chair Rankings (X) Agency Rankings (Y)
2 4
1 3
3 1
4.5 2
4.5 5
7 10
8 7
6 7
9 7
10 9









6. Effect of range on correlation

A. Restricted range















7. Correlation and causation

X Y















Statistics