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Lecture 6

# PSYC 2030 Lecture Notes - Lecture 6: Descriptive Statistics, X&Y

Department
Psychology
Course Code
PSYC 2030
Professor
Rebecca Jubis
Lecture
6

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PSYC 2030
February 17,2017
The Correlation Coefficient
A positive relationship states that if one variable increases then the corresponding variable
also increases and vice versa for the negative variable. The typically used coefficient is
Pearson r unless otherwise indicated it is appropriate to use this if there I an interval or
ratio scale. It is a descriptive statistic that describe the characteristics of the data coefficient
describes the relationship of the two variables.
Restriction of Range is when only a narrow range of scores are used for both variables
and this misrepresents the correlation and reduces the ability to make predictions
An outlier is a score that is extremely different form the others in the data set and can
distort the correlation coefficient.
Regression Analysis (line of the best fit)
- This involves making predictions on the basis of correlational data.
- Knowing the size of the correlation ad a value for xpredictor variable, it is
possible to predict the value from ycriterion variable
- Minimizes the vertical distances in all of the dots
Multiple Regression- 2 predictor variables
Coefficient of Determination
- to calculate all you do is take the coefficient r and square it
- It indicates the proportion of variants in one variable that can be accounted for by
another variable
r= +.25 is interpreted as one increases so does the other but the relationship is weak and
cannot be predicted
r squared = 0.625 = 6.25% very weak
second example
r= +.90
r squared = 81%
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