Chapter12 - CHAPTER 12 Section 12.1 1. a. Stem and Leaf...

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351 CHAPTER 12 Section 12.1 1. a. Stem and Leaf display of temp: 17 0 17 23 stem = tens 17 445 leaf = ones 17 67 17 18 0000011 18 2222 18 445 18 6 18 8 180 appears to be a typical value for this data. The distribution is reasonably symmetric in appearance and somewhat bell-shaped. The variation in the data is fairly small since the range of values ( 188 – 170 = 18) is fairly small compared to the typical value of 180. 0 889 1 0000 stem = ones 1 3 leaf = tenths 1 4444 1 66 1 8889 2 11 2 2 5 2 6 2 3 00 For the ratio data, a typical value is around 1.6 and the distribution appears to be positively skewed. The variation in the data is large since the range of the data (3.08 - .84 = 2.24) is very large compared to the typical value of 1.6. The two largest values could be outliers. b. The efficiency ratio is not uniquely determined by temperature since there are several instances in the data of equal temperatures associated with different efficiency ratios. For example, the five observations with temperatures of 180 each have different efficiency ratios.
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Chapter 12: Simple Linear Regression and Correlation 352 c. A scatter plot of the data appears below. The points exhibit quite a bit of variation and do not appear to fall close to any straight line or simple curve. 2. Scatter plots for the emissions vs age: With this data the relationship between the age of the lawn mower and its NO x emissions seems somewhat dubious. One might have expected to see that as the age of the lawn mower increased the emissions would also increase. We certainly do not see such a pattern. Age does not seem to be a particularly useful predictor of NO x emission. 170 180 190 1 2 3 Temp: Ratio: 0 5 1 0 1 5 0 1 2 3 4 5 Age: Baseline 15 1 0 5 0 7 6 5 4 3 2 1 0 Age: Reformul
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Chapter 12: Simple Linear Regression and Correlation 353 3. A scatter plot of the data appears below. The points fall very close to a straight line with an intercept of approximately 0 and a slope of about 1. This suggests that the two methods are producing substantially the same concentration measurements. 50 100 150 200 20 120 220 x: y: 4. a. Box plots of both variables: On both the BOD mass loading boxplot and the BOD mass removal boxplot there are 2 outliers. Both variables are positively skewed. 0 10 20 30 40 50 60 70 80 90 y: BOD mass removal 0 50 100 150 x: BOD mass loading
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Chapter 12: Simple Linear Regression and Correlation 354 b. Scatter plot of the data: There is a strong linear relationship between BOD mass loading and BOD mass removal. As the loading increases, so does the removal. The two outliers seen on each of the boxplots are seen to be correlated here. There is one observation that appears not to match the liner pattern. This value is (37, 9). One might have expected a larger value for BOD mass removal. 5.
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This note was uploaded on 03/30/2008 for the course STAT 211 taught by Professor Parzen during the Spring '07 term at Texas A&M.

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Chapter12 - CHAPTER 12 Section 12.1 1. a. Stem and Leaf...

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