Quick Review Of Some Inference For Linear Regression Concepts

7 Questions | Total Attempts: 164

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Inference Quizzes & Trivia

Inference and modeling concepts for AP Statistics students


Questions and Answers
  • 1. 
    How do you know that you should attempt to use a linear regression method for predicting y values from x values?
    • A. 

      When the moon is full.

    • B. 

      When Mrs. Linner gives you the evil eye.

    • C. 

      When the data look linear when graphed in a scatterplot.

    • D. 

      When the relationship should (theoretically) be linear.

    • E. 

      Either C or D will suffice.

  • 2. 
    How do you know that your linear model was a wise choice (the linear model is the correct model)?
    • A. 

      When I flip a coin and it lands heads up.

    • B. 

      When I have run out of other models to try.

    • C. 

      When the r^2 value is close to 1.

    • D. 

      When the graph of the residuals(x, y - y-hat)forms a straight line.

    • E. 

      When the residuals(x, y - y-hat)are small and scattered(no pattern).

  • 3. 
    When do you know that the model is a close fit to the data?
    • A. 

      When I flip a coin and it lands heads up.

    • B. 

      When I have run out of other models to try.

    • C. 

      When the r^2 value is close to 1.

    • D. 

      When the graph of the residuals(x, y - y-hat)forms a straight line.

    • E. 

      When the residuals(x, y - y-hat)are small and scattered(no pattern).

  • 4. 
    When is the relationship between x and y too strong to assume that the slope of the best fit line (Beta) is possibly zero?
    • A. 

      When the confidence interval for the slope does not contain the value 0.

    • B. 

      When the p value of the linear regression t-test is very small.

    • C. 

      When the residuals are small and scattered.

    • D. 

      When the r^2 value is close to 1

    • E. 

      Answers A or B will suffice.

  • 5. 
    Given r, sx, and sy you can calculate
    • A. 

      Beta

    • B. 

      Alpha

    • C. 

      B

    • D. 

      S

    • E. 

      SE of b

  • 6. 
    Given s, sx, and n you can calculate
    • A. 

      Beta

    • B. 

      Alpha

    • C. 

      B

    • D. 

      R

    • E. 

      SE of b

  • 7. 
    Given b and SE of b you still need to know _______________ to calculate the t-statistic and the p-value.
    • A. 

      R

    • B. 

      N

    • C. 

      Df

    • D. 

      A

    • E. 

      B or C