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QMB3250 Exam 3 UF questions with complete and correct answers
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QMB3250 Exam 3 UF questions with complete and correct answers
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QMB3250 Exam 3 UF questions withcomplete and correct answers
One-way ANOVA test null hypothesis - ANSWER: ➡ M1=M2=M3=M4....
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tests the difference between population means, so we are looking to see if the difference is not
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equal
o
replicates formula - ANSWER: ➡ # of experamental units o o o oo o o o o
--------------------------
# of treatments
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interaction null and alternate hypothesis - ANSWER: ➡ Ho: Interaction is not significant
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Ha: Interaction is significant
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advantages of studying two factors simultaneously in an experiment?... - ANSWER: ➡ a) It is
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more efficient to study two factors simultaneously rather than separately.
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b) We can reduce the residual variation in a model by including a second factor thought to
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influence the response.
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c) We can investigate interaction between factors
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multiple regression? - ANSWER: ➡ two quantitative variables predicting a third quantitative
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variable
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two way ANOVA - ANSWER: ➡ two factors
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, one way ANOVA - ANSWER: ➡ one factor
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another name for residuals? - ANSWER: ➡ error
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(i.e. DFE -> degrees of freedom error)
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to find degrees of freedom total from an ANOVA table?... - ANSWER: ➡ take the total degrees of
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freedom and add 1
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what does it mean if 0 is included in the confidence interval? - ANSWER: ➡ that there is a
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statistically significant difference
o o o
What does N and n represent in Kruscall Walis test? - ANSWER: ➡ N - total number in sample
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n - number in each group
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what is a dead giveaway for multicollenierity? - ANSWER: ➡ when you have an overall F
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statistic that shows that you have a significant model, but the p-values state that none of the
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variables contribute to the model
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what does it mean if there is a squared predictor? - ANSWER: ➡ the shape of the line is
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quadratic
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what do you do with the interaction variable when using the line equation?... - ANSWER: ➡ y-
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hat = intercept +/- X1(x1) +/- X2(x2) +/- interaction variable (x1)(x2)
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Backwards Elimination - ANSWER: ➡ Fit Model > Enter Y and All Predictor Variables >
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Change box in top right to Stepwise. Select
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