StatTutor Lesson - Checking the Conditions for Inference

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StatTutor: Checking the conditions for inference
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      Question 1

      39

      Question 1.

      What is a residual?

      A.
      B.
      C.

      Correct. Residual equals observed y minus predicted y or y - y^.
      Incorrect. Residual equals observed y minus predicted y or y - y^.
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      Question 2

      72

      Question 2.

      Fill in the blank: A residual plot is a scatterplot of the ____________ versus the observed x values.

      A.
      B.

      Correct. A residual plot is a scatterplot of residuals versus observed x values. It is NOT a scatterplot of the observed y values versus the observed x values.
      Incorrect. A residual plot is a scatterplot of residuals versus observed x values. It is NOT a scatterplot of the observed y values versus the observed x values.
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      Question 3

      115

      Question 3.

      True or false: We can use a residual plot to check for problems with linearity and equal standard deviation.

      A.
      B.

      Correct. This is a correct statement.
      Incorrect. This is a correct statement.
      2
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      Question 4

      148

      Question 4.

      What indicates non-linearity?

      A.
      B.
      C.

      Correct. A smile or frown pattern in a residual plot indicates non-linearity.
      Incorrect. A smile or frown pattern in a residual plot indicates non-linearity.
      2
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      Question 5

      174

      Question 5.

      What indicates unequal standard deviation?

      A.
      B.
      C.

      Correct. A megaphone pattern in the residual plot indicates unequal variation in the y’s for all x values.
      Incorrect. A megaphone pattern in the residual plot indicates unequal variation in the y’s for all x values.
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      Question 6

      211

      Question 6.

      What indicates non-Normality?

      A.
      B.
      C.

      Correct. As with other t procedures an outlier or strong skewness indicates non-Normality.
      Incorrect. As with other t procedures an outlier or strong skewness indicates non-Normality.
      2
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      Question 7

      235

      Question 7.

      Why is Normality ok for these data?

      A.
      B.

      Correct. With n = 92, the sample size is large enough to apply the Central Limit Theorem so Normality is ok.
      Incorrect. With n = 92, the sample size is large enough to apply the Central Limit Theorem so Normality is ok.
      2
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      Question 8

      304

      Question 8.

      True or false: Checks for independence are beyond the scope of this course.

      A.
      B.

      Correct. This is a correct statement.
      Incorrect. This is a correct statement.
      2
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      Question 9

      322

      Question 9.

      Do these plots indicate non-linearity with a smile or frown pattern?

      A.
      B.

      Correct. Since we don’t see curvature in the scatterplot and we don’t see a smile or frown pattern in the residual plot, these plots do not indicate non-linearity.
      Incorrect. Since we don’t see curvature in the scatterplot and we don’t see a smile or frown pattern in the residual plot, these plots do not indicate non-linearity.
      2
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      Questions 10-11

      336

      Question 10.

      Do these plots indicate non-linearity with a smile or frown pattern?

      A.
      B.

      Correct. Since we see curvature in the scatterplot and we see a smile pattern in the residual plot, these plots do indicate non-linearity.
      Incorrect. Since we see curvature in the scatterplot and we see a smile pattern in the residual plot, these plots do indicate non-linearity.
      2
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      Questions 12-13

      364

      Question 12.

      Do these plots indicate non-linearity with a smile or frown pattern?

      A.
      B.

      Correct. Since we don’t see curvature in the scatterplot and we don’t see a smile or frown pattern in the residual plot, these plots do not indicate non-linearity.
      Incorrect. Since we don’t see curvature in the scatterplot and we don’t see a smile or frown pattern in the residual plot, these plots do not indicate non-linearity.
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      Questions 14-15

      378

      Question 14.

      Do these plots indicate non-linearity with a smile or frown pattern?

      A.
      B.

      Correct. Since we don’t see curvature in the scatterplot and we don’t see a smile or frown in the residual plot, these plots do not indicate non-linearity.
      Incorrect. Since we don’t see curvature in the scatterplot and we don’t see a smile or frown in the residual plot, these plots do not indicate non-linearity.
      2
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      Question 16

      391

      Question 16.

      Does this plot indicate non-Normality?

      A.
      B.

      Correct. With sample size n = 9, the outlier in this histogram of the residuals indicates lack of Normality.
      Incorrect. With sample size n = 9, the outlier in this histogram of the residuals indicates lack of Normality.
      2
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