# Chapter 1. Checking the Conditions for Inference

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0:39

### Question 1.1

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Correct. Residual equals observed y minus predicted y or y - $$\widehat{y}$$.
Incorrect. Residual equals observed y minus predicted y or y - $$\widehat{y}$$.
2
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1:12

### Question 1.2

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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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1:55

### Question 1.3

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Correct. This is a correct statement.
Incorrect. This is a correct statement.
2
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2:28

### Question 1.4

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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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2:54

### Question 1.5

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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.
2
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3:31

### Question 1.6

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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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3:55

### Question 1.7

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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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5:04

### Question 1.8

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Correct. This is a correct statement.
Incorrect. This is a correct statement.
2
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5:22

### Question 1.9

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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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5:36

### Question 1.10

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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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### Question 1.11

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Correct. Since we don’t see a megaphone in the residual plot, these plots do not indicate non-constant standard deviation.
Incorrect. Since we don’t see a megaphone in the residual plot, these plots do not indicate non-constant standard deviation.
2
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6:04

### Question 1.12

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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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### Question 1.13

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Correct. Since we don’t see a megaphone in the residual plot, these plots do not indicate non-constant standard deviation.
Incorrect. Since we don’t see a megaphone in the residual plot, these plots do not indicate non-constant standard deviation.
2
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6:18

### Question 1.14

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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 1.15

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Correct. Since we see a megaphone pattern in both the scatterplot and the residual plot, these plots indicate non-constant standard deviation.
Incorrect. Since we see a megaphone pattern in both the scatterplot and the residual plot, these plots indicate non-constant standard deviation.
2
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6:31

### Question 1.16

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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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