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# The article Multiple Linear Regression for Lake Ice and Lake Temperature Characteristics ISBN: 9780073401331 38

## Solution for problem 18 Chapter 8.1

Statistics for Engineers and Scientists | 4th Edition

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Problem 18

The article Multiple Linear Regression for Lake Ice and Lake Temperature Characteristics (S. Gao and H. Stefan, Journal of Cold Regions Engineering, 1999:5977) presents data on maximum ice thickness in mm (y), average number of days per year of ice cover (x1), average number of days the bottom temperature is lower than 8C (x2), and the average snow depth in mm (x3) for 13 lakes in Minnesota. The data are presented in the following table. y x1 x2 x3 y x1 x2 x3 730 152 198 91 730 157 204 90 760 173 201 81 650 136 172 47 850 166 202 69 850 142 218 59 840 161 202 72 740 151 207 88 720 152 198 91 720 145 209 60 730 153 205 91 710 147 190 63 840 166 204 70 a. Fit the model y = 0+1 x1+2 x2+3 x3+. For each coefficient, find the P-value for testing the null hypothesis that the coefficient is equal to 0. b. If two lakes differ by 2 in the average number of days per year of ice cover, with other variables being equal, by how much would you expect their maximum ice thicknesses to differ? c. Do lakes with greater average snow depth tend to have greater or lesser maximum ice thickness? Explain.

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Stats notes 1 Population- includes all individuals or objects of interest Sample- subset of the population EXAMPLE: Population: all 3,000 the people attending a concert Sample: a small section of 500 people that attended Cases- what we’re obtaining information on Variables- any characteristic that...

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##### ISBN: 9780073401331

The full step-by-step solution to problem: 18 from chapter: 8.1 was answered by , our top Statistics solution expert on 06/28/17, 11:15AM. This full solution covers the following key subjects: . This expansive textbook survival guide covers 153 chapters, and 2440 solutions. This textbook survival guide was created for the textbook: Statistics for Engineers and Scientists , edition: 4. Statistics for Engineers and Scientists was written by and is associated to the ISBN: 9780073401331. Since the solution to 18 from 8.1 chapter was answered, more than 232 students have viewed the full step-by-step answer. The answer to “The article Multiple Linear Regression for Lake Ice and Lake Temperature Characteristics (S. Gao and H. Stefan, Journal of Cold Regions Engineering, 1999:5977) presents data on maximum ice thickness in mm (y), average number of days per year of ice cover (x1), average number of days the bottom temperature is lower than 8C (x2), and the average snow depth in mm (x3) for 13 lakes in Minnesota. The data are presented in the following table. y x1 x2 x3 y x1 x2 x3 730 152 198 91 730 157 204 90 760 173 201 81 650 136 172 47 850 166 202 69 850 142 218 59 840 161 202 72 740 151 207 88 720 152 198 91 720 145 209 60 730 153 205 91 710 147 190 63 840 166 204 70 a. Fit the model y = 0+1 x1+2 x2+3 x3+. For each coefficient, find the P-value for testing the null hypothesis that the coefficient is equal to 0. b. If two lakes differ by 2 in the average number of days per year of ice cover, with other variables being equal, by how much would you expect their maximum ice thicknesses to differ? c. Do lakes with greater average snow depth tend to have greater or lesser maximum ice thickness? Explain.” is broken down into a number of easy to follow steps, and 216 words.

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