Experimental Design Data Normal Distribution 1st Half Review Experimental Design Data Normal Distribution

Types of Experiments Mensurative Manipulative Take advantage of existing variability in predictor Manipulative Actively change the values of the predictor

Treatments and Controls Specific condition applied to all members of a group Control A group that does not receive the condition

Entities, Variables, and Values Entity – thing or group of things we want to ask questions about Variable – Character of entity we are going to measure Value – result of measurement of variable Entity Variable Value

More on Variables Ratio vs Interval vs Ordinal vs Nominal Continuous vs Discrete Precision vs Accuracy

Frequency Distribution occurrence of the various values observed for the variable raw frequency counts relative frequency counts divided by total number of observations

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Central Tendency Measures Mean vs Median vs Mode

Measures of Dispersion Deviation & Absolute Deviation from Mean Sum of Squares Variance & Standard Deviation Coefficient of Variation

Normal Distribution X The Standardized Normal Curve

Standard Normal Deviate  68% 95% 99.7% -3 -2 -1 1 2 3

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More than One Sample Mean of the Means Variance of the Means Standard deviation of the mean or the Standard error of the mean

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Hypothesis Testing    0.95 Hypothesis about population  Not Sample Null vs Alternate Hypothesis, One vs Two Tails When do we reject??  0.95  

Types of Error and other Things Type I vs Type II Power Significance Level What is p??? What is α?? What is β??

t-Test When do we use t-Test???

Critical t’s What effects critical t-value When do we reject null?? df & p When do we reject null?? Two-Tail if |tobserved|  tcritical; reject H0 One-Tail ???

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Confidence interval for t What does it mean?? What effects it??

Two-Sample t-Test When do we use?? Null Hypothesis?? Standard error of the difference between the means

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ANOVA Variance Partitions Total = Among + Within Grand Mean, Group Mean and associated Deviations When do we reject based on variance ratio???

ANOVA When do we use?? Model I vs Model II vs Model III?? Multi-Factors?? Main Effects vs Interactions??

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