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I. Establishing Relations Among Variables

A. Variable

1. Dimension along which variations exists

2. Must be at least two values or levels on that dimension, though some

variables have an infinite number of values

a) Example

(1) Sex; female and male

(2) Self esteem; ranges from high to low

B. Correlation between Variables

1. Correlation

a) Two kinds of relationship that can be found between variables

b) Correlation between two dimensions means that you can examine

them across many examples or instances

2. Values tend to go together in a systematic way

a) two aspect of this relationship

(1) Direction of the correlation

(a) Positive versus negative

(i) Two variables are said to be positively

correlated if lows tend to go with lows or

highs tend to go with highs

(ii) Inverse or negative correlation is when a the

two dimensions are opposite in direction

(high and low)

(2) the strength of the correlation

(a) Sloppiness of the association between the

variables

(b) Refers to the degree of accuracy with which you

can predict values on one dimension from values

on the other dimensions

(c) Correlation coefficient

(i) Labeled with lowercase r

(ii) 1.0 is the largest numerical value a

correlation can take

(iii) The closer to 1.0, the stronger the strength

regardless if it’s positive or negative

3. Organizing Data

a) Scatterplot

(1) Two variables are represented by lines at right angles

(2) Points where the lines meet is zero for both variables

(3) Being farther away tom zero on each lime means having a

higher value on that variable

C. Two kinds of Significance

1. Statistically significant

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