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Open the dataset of FamilySedans (attached) Use descriptive statistics to summarize the data and make comments on them. 2. Use regression analysis to develop an estimated regression equation that could be used to predict the value score given the price of the car. Use regression analysis to develop an estimated regression equation that could be used to predict the value score given the five-year ow

Open the dataset of FamilySedans (attached) Use descriptive statistics to summarize the data and make comments on them. 2. Use regression analysis to develop an estimated regression equation that could be used to predict the value score given the price of the car. Use regression analysis to develop an estimated regression equation that could be used to predict the value score given the five-year ow

Algebra & Trigonometry with Analytic Geometry
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter8: Applications Of Trigonometry
Section8.2: The Law Of Cosines
Problem 3E
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1. Open the dataset of FamilySedans (attached) Use descriptive statistics to summarize the data and make comments on them.

2. Use regression analysis to develop an estimated regression equation that could be used to predict the value score given the price of the car. Use regression analysis to develop an estimated regression equation that could be used to predict the value score given the five-year owner costs.

3. Use regression analysis to develop an estimated regression equation that could be used to predict the value score given the road-test score. Use regression analysis to develop an estimated regression equation that could be used to predict the value score given the predicted-reliability.

4. What conclusions can you derive from your analysis?

A C D E F Road- Cost/ Test Predicted Value 1 Car 2 Nissan Altima 2.5 S (4-cyl.) 3 Kia Optima LX (2.4) 4 Subaru Legacy 2.5i Premium 5 Ford Fusion Hybrid 6 Honda Accord LX-P (4-cyl.) 7 Mazda6 i Sport (4-cyl.) Price ($) Mile Score Reliability Score 23,970.00 0.59 91 4 1.75 21,885.00 0.58 81 4 1.73 23,830.00 0.59 83 4 1.73 32,360.00 0.63 84 5 1.70 23,730.00 0.56 80 4 1.62 22,035.00 0.58 73 4 1.60 8 Hyundai Sonata GLS (2.4) 9 Ford Fusion SE (4-cyl.) 10 Chevrolet Malibu LT (4-cyl.) 21,800.00 0.56 89 3 1.58 23,625.00 0.57 76 4 1.55 24,115.00 0.57 74 3 1.48 11 Kia Optima SX (2.0T) 12 Ford Fusion SEL (V6) 13 Nissan Altima 3.5 SR (V6) 29,050.00 0.72 84 4 1.43 28,400.00 0.67 80 4 1.42 30,335.00 0.69 93 4 1.42 14 Hyundai Sonata Limited (2.0T) 28,090.00 0.66 15 Honda Accord EX-L (V6) 89 3 1.39 28,695.00 0.67 90 3 1.36 16 Mazda6 s Grand Touring (V6) 30,790.00 0.74 17 Ford Fusion SEL (V6, AWD) 30,055.00 0.71 18 Subaru Legacy 3.6R Limited 19 Chevrolet Malibu LTZ (V6) 81 4 1.34 75 4 1.32 30,094.00 0.71 88 3 1.29 28,045.00 0.67 83 3 1.20 20 Chrysler 200 Limited (V6) 21 Chevrolet Impala LT (3.6) 27,825.00 0.70 52 1.20 28,995.00 0.67 63 3 1.05 22
Transcribed Image Text:A C D E F Road- Cost/ Test Predicted Value 1 Car 2 Nissan Altima 2.5 S (4-cyl.) 3 Kia Optima LX (2.4) 4 Subaru Legacy 2.5i Premium 5 Ford Fusion Hybrid 6 Honda Accord LX-P (4-cyl.) 7 Mazda6 i Sport (4-cyl.) Price ($) Mile Score Reliability Score 23,970.00 0.59 91 4 1.75 21,885.00 0.58 81 4 1.73 23,830.00 0.59 83 4 1.73 32,360.00 0.63 84 5 1.70 23,730.00 0.56 80 4 1.62 22,035.00 0.58 73 4 1.60 8 Hyundai Sonata GLS (2.4) 9 Ford Fusion SE (4-cyl.) 10 Chevrolet Malibu LT (4-cyl.) 21,800.00 0.56 89 3 1.58 23,625.00 0.57 76 4 1.55 24,115.00 0.57 74 3 1.48 11 Kia Optima SX (2.0T) 12 Ford Fusion SEL (V6) 13 Nissan Altima 3.5 SR (V6) 29,050.00 0.72 84 4 1.43 28,400.00 0.67 80 4 1.42 30,335.00 0.69 93 4 1.42 14 Hyundai Sonata Limited (2.0T) 28,090.00 0.66 15 Honda Accord EX-L (V6) 89 3 1.39 28,695.00 0.67 90 3 1.36 16 Mazda6 s Grand Touring (V6) 30,790.00 0.74 17 Ford Fusion SEL (V6, AWD) 30,055.00 0.71 18 Subaru Legacy 3.6R Limited 19 Chevrolet Malibu LTZ (V6) 81 4 1.34 75 4 1.32 30,094.00 0.71 88 3 1.29 28,045.00 0.67 83 3 1.20 20 Chrysler 200 Limited (V6) 21 Chevrolet Impala LT (3.6) 27,825.00 0.70 52 1.20 28,995.00 0.67 63 3 1.05 22
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