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