In a recent survey, ice cream truck drivers in Cincinnati, Ohio, reported that they make about $280 in income on a typical summer day. The income was generally higher on days with longer work hours, particularly hot days, and on holidays. The accompanying data file includes five weeks of the driver’s daily income (Income), number of hours on the road (Hours), whether it was a particularly hot day (Hot = 1 if the high temperature was above 85°F, 0 otherwise), and whether it was a Holiday (Holiday = 1, 0 otherwise). Income Hours Hot Holiday 196 5 1 0 282 8 0 0 318 6 1 0 232 5 1 0 276 8 0 0 312 8 0 1 193 5 0 1 110 4 0 0 321 8 1 0 283 8 0 0 325 8 1 0 247 7 0 1 398 8 1 1 448 8 1 1 214 4 0 0 235 8 0 0 238 8 0 0 148 3 1 0 313 8 0 1 449 8 1 1 332 8 1 1 247 8 0 0 363 7 1 0 393 7 1 1 254 8 0 0 228 8 0 0 355 6 1 1 248 7 0 1 291 8 1 0 255 5 1 0 239 6 0 0 181 6 0 0 222 7 0 0 170 5 0 1 374 6 1 1 1. Estimate the effect of Hours, Hot, and Holidays on Income. Report the regression coefficients and their significance at the 5% level. Note: Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.   2. Predict the income of a driver under the following scenarios. Note: Round coefficient estimates to at least 4 decimal places and final answer to 2 decimal places. Predictor Vairables Predicted y Hours =6; Hot; Holiday Hours =6; Hot; Non-Holiday    3. Extend the above model to include the interaction between Hot and Holiday. Report the regression coefficients and their significance at the 5% level. Note: Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.   4. Predict the income of a driver under the following scenarios. Note: Round coefficient estimates to at least 4 decimal places and final answer to 2 decimal places. Predictor Vairables Predicted y Hours =6; Hot; Holiday Hours =6; Hot; Non-Holiday

MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
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In a recent survey, ice cream truck drivers in Cincinnati, Ohio, reported that they make about $280 in income on a typical summer day. The income was generally higher on days with longer work hours, particularly hot days, and on holidays. The accompanying data file includes five weeks of the driver’s daily income (Income), number of hours on the road (Hours), whether it was a particularly hot day (Hot = 1 if the high temperature was above 85°F, 0 otherwise), and whether it was a Holiday (Holiday = 1, 0 otherwise).

Income Hours Hot Holiday
196 5 1 0
282 8 0 0
318 6 1 0
232 5 1 0
276 8 0 0
312 8 0 1
193 5 0 1
110 4 0 0
321 8 1 0
283 8 0 0
325 8 1 0
247 7 0 1
398 8 1 1
448 8 1 1
214 4 0 0
235 8 0 0
238 8 0 0
148 3 1 0
313 8 0 1
449 8 1 1
332 8 1 1
247 8 0 0
363 7 1 0
393 7 1 1
254 8 0 0
228 8 0 0
355 6 1 1
248 7 0 1
291 8 1 0
255 5 1 0
239 6 0 0
181 6 0 0
222 7 0 0
170 5 0 1
374 6 1 1

1. Estimate the effect of Hours, Hot, and Holidays on Income. Report the regression coefficients and their significance at the 5% level.

Note: Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.

 

2. Predict the income of a driver under the following scenarios.

Note: Round coefficient estimates to at least 4 decimal places and final answer to 2 decimal places.

Predictor Vairables Predicted y
Hours =6; Hot; Holiday
Hours =6; Hot; Non-Holiday

 

 3. Extend the above model to include the interaction between Hot and Holiday. Report the regression coefficients and their significance at the 5% level.

Note: Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.

 

4. Predict the income of a driver under the following scenarios.

Note: Round coefficient estimates to at least 4 decimal places and final answer to 2 decimal places.

Predictor Vairables Predicted y
Hours =6; Hot; Holiday
Hours =6; Hot; Non-Holiday
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