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Four Basic Canons of Science
- Determinism: Events have meaningful, systematic causes.
- Empiricism: The method of making observations. (Making observations is the best method.)
- Parsimony: If we have two competing theories, we should choose the simpler or more frugal of the two.
- Testability: You must be able to realistically test the theory (involves Validation, Falsification & Qualification).
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Quasi-Experiment
Naturally occurring grouping variable, but analyzed like an experiment.
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Independent variables vs. grouping variables
- Variable that is manipulated by experimenter
- In a Quasi-experiment, called the grouping variable (GV)
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Scales of Measurement: NOIR
- Nominal: – Numbers are names only, no real order.
- – Use Frequencies and Chi-Square
- Ordinal:– rank ordered, but don’t know how far apart scores are.
- Sprite is favorite, coke is 2nd
- Interval:– Tells how far apart values are, but no true 0 point. Equal interval between units.
- Sprite>Coke>>>>Pepsi>>>>>>>Tea
- Ratio: – like interval but with a true 0 point
- Temperature
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Descriptive Statistics
- Measures of Central tendency: Mean, median, mode
- Measures of Variability: Range, variance, standard deviation
- Range is the difference between the largest and smallest value
- Variance is the average squared deviation of each score from the mean
- Standard deviation is the square root of the variance.
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Type I and Type II errors
Type I error: a true null hypothesis is rejected (false positive)
Type II error: Failing to regect a false null (false negative)
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Factors, levels, and between/within- subjects
designs
- Factors: # of IVs
- Levels: Treatment conditions PER IV
- Between/Within Group: Between- People are in different groups. Within- People test out all groups and compare to self.
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Generalizability
- Statistical generalizability: Allows you to generalize to the population from which you randomly selected.
- Practical generalizability: You can generalize to similar individuals (i.e., college students)
- Situational Generalizability: Can findings from the lab be applied to real life? How is the research setting different from other settings? How were the variables (IV’s & DV’s) operationalized?
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Grouping variable
- Typically categorical
- Male, female
- 1, 2, 3, 4
- etc
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The Values
- T= Grand Total
- t= # of grand totals (always 1)
- A= Total for each condition
- a= # of levels for the IV
- AS= Individual scores
- s= # of participants per condition
- as= Total # of participants
- [T]=T2/as
- [A]=A12+A22/s
- [AS]=AS2
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