3/19/2020 Exam 2 – Review Sheet: SRA 365, Section 001 and 002: Stat Sec and Rsk Anl, FA19 Hamilton WC
https://psu.instructure.com/courses/2019907/pages/exam-2-review-sheet?module_item_id=27312562 1/2
Exam 2 – Review Sheet
Please be sure you have a good understanding of the following material before completing Exam
2.
Lesson 5
Know how to write syntax to run a simple regression model in R
Be able to report and interpret the following in the results
the regression model/equation
the variability in Y that can be explained by X
the variability in Y that cannot be explained by X
the statistical significance of the model/equation
Know how to generate prediction and confidence intervals in R and explain the difference
between the two
Lesson 6
Know how to write syntax to evaluate the following three assumptions in R
Independence of observations
Homogeneity of variance
Normality
Know the cutoffs and other decision points used to determine if any of these assumptions
have been violated
Understand the three main cautions of regression and be able to tell if any of them have been
violated
Lesson 7
Know how to write syntax to do the following in R
execute the best subsets approach
run a multiple regression model
evaluate multicollinearity
Know how to identify the best models displayed in the subsets plot based on their predictors
and Adjusted R
Be able to report and interpret the following results from your multiple regression analysis
the regression model/equation
the variability in Y that can be explained by all the X variables combined
the statistical significance of the model/equation
the statistical significance of the individual predictors
2
3/19/2020 Exam 2 – Review Sheet: SRA 365, Section 001 and 002: Stat Sec and Rsk Anl, FA19 Hamilton WC
https://psu.instructure.com/courses/2019907/pages/exam-2-review-sheet?module_item_id=27312562 2/2
Know the cutoffs used to determine if multicollinearity has been violated based on the VIF,
tolerance, and correlation matrix
Lesson 8
Understand the differences between categorical and continuous variables (also see L01 for a
review of this)
Be able to determine how many dummy variables would be needed based on the number of
subcategories in a variable
Know how to write syntax to do the following in R
run a regression analysis with dummy variables
produce the mean levels of the outcome for each dummy variable
Be able to interpret:
the significance of the regression model
the significance of the predictors
the direction of the means
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