PSYC 1101 Lecture Notes - Lecture 5: Illusory Correlation, Inverse Relation, Frequency Distribution

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Correlational research
Research project that investigates the degree to which two variables are related to each
other
Does NOT say that one variable causes another
Pros determines relationship between 2 variables. Predicts future behavior
Cons will uncover a relationship but that does not mean it is the cause
Correlations also vary in the strength of the association
Zero correlation no relationship between the 2 variables
Strong correlation knowing the value of one variable permits one to accurately
estimate the value of the other variable
Strong correlation can be positive or negative
Correlations can be seen in scatter plots
The terms positive and negative describe the direction of the relationship, not whether or
not something is good or bad
Perfect positive correlation direct relation
Perfect negative correlation inverse relation
No relationship correlation
The closer to 1, the stronger the correlation (only between -1 to 1)
For example a -0.91 indicates a stronger relationship than +0.3
Illusory correlation
The perception of a relationship where none exists
Ex: stereotypes
Descriptive statistic
Statistics allow psychologists to
Organize data
Present data in ways that are easier to comprehend
Describe data
Make inferences based upon data
Frequency distributions
Frequency is how often something occurs
Frequency distribution list of scores from highest to lowest
What type of graph would you use to show a frequency distribution?
Examples:
Scores from the Psychology final pretest
Measures of central tendency
AKA: mean, median, and mode
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Document Summary

Research project that investigates the degree to which two variables are related to each other. Does not say that one variable causes another. Pros determines relationship between 2 variables. Cons will uncover a relationship but that does not mean it is the cause. Correlations also vary in the strength of the association. Zero correlation no relationship between the 2 variables. Strong correlation knowing the value of one variable permits one to accurately estimate the value of the other variable. Strong correlation can be positive or negative. Correlations can be seen in scatter plots. The terms positive and negative describe the direction of the relationship, not whether or not something is good or bad. The closer to 1, the stronger the correlation (only between -1 to 1) For example a -0. 91 indicates a stronger relationship than +0. 3. The perception of a relationship where none exists. Present data in ways that are easier to comprehend.

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