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Use Excel Megastat values or partial output to answer the following questions. A

ID: 3231392 • Letter: U

Question

Use Excel Megastat values or partial output to answer the following questions. Add units of measurement and interpret numerical results whenever possible.

Your answers must be full and complete in order to receive credit.

Treadmills Case:

Consumer Reports provided extensive testing and ratings for 24 treadmills. An overall score, based primarily on ease of use, ergonomics, exercise range, and quality, was developed for each treadmill tested. In general, a higher overall score indicates better performance. The following data (Excel file available in Connect “Lab assignment 5” folder) contains data on the price, overall score, and quality rating for the 24 treadmills (Consumer Reports, February 2006).

Use the “good” quality rating as the base when creating the dummy variables for quality.

Brand & Model

Price ($)

Score (points)

Quality

Landice L7

2900

86

Excellent

NordicTrack S3000

3500

85

Very good

SportsArt 3110

2900

82

Excellent

Precor

3500

81

Excellent

True Z4 HRC

2300

81

Excellent

Vision Fitness T9500

2000

81

Excellent

Precor M 9.31

3000

79

Excellent

Vision Fitness T9200

1300

78

Very good

Star Trac TR901

3200

72

Very good

Trimline T350HR

1600

72

Very good

Schwinn 820p

1300

69

Very good

Bowflex 7-Series

1500

83

Excellent

NordicTrack S1900

2600

83

Very good

Horizon Fitness PST8

1600

82

Very good

Horizon Fitness 5.2T

1800

80

Very good

Evo by Smooth Fitness FX30

1700

75

Very good

ProForm 1000S

1600

75

Very good

Horizon Fitness CST4.5

1000

74

Very good

Keys Fitness 320t

1200

73

Very good

Smooth Fitness 7.1HR Pro

1600

73

Very good

NordicTrack C2300

1000

70

Good

Spirit Inspire

1400

70

Very good

ProForm 750

1000

67

Good

Image 19.0 R

600

66

Good

A.) Using Excel Megastat output, report multiple regression equation for predicting the price of treadmills when knowing their overall score and quality rating.

B.) Interpret the meaning of each of the regression coefficient starting with b0 as an estimate of 0, and continuing with b1, b2…. For each “bn” report a value and which “X” is it a coefficient for.

1a. Partial regression coefficient for the y-intercept, b0 = _______

1b. interpretation of b0 –

1c. Does the interpretation of the y-intercept make sense? Why yes/no?

2a. Partial regression coefficient for X1 (score in points), b1 = ________

2b. Interpretation of b1 –

...Continue in the same fashion until you have interpreted all partial regression coefficients

Brand & Model

Price ($)

Score (points)

Quality

Landice L7

2900

86

Excellent

NordicTrack S3000

3500

85

Very good

SportsArt 3110

2900

82

Excellent

Precor

3500

81

Excellent

True Z4 HRC

2300

81

Excellent

Vision Fitness T9500

2000

81

Excellent

Precor M 9.31

3000

79

Excellent

Vision Fitness T9200

1300

78

Very good

Star Trac TR901

3200

72

Very good

Trimline T350HR

1600

72

Very good

Schwinn 820p

1300

69

Very good

Bowflex 7-Series

1500

83

Excellent

NordicTrack S1900

2600

83

Very good

Horizon Fitness PST8

1600

82

Very good

Horizon Fitness 5.2T

1800

80

Very good

Evo by Smooth Fitness FX30

1700

75

Very good

ProForm 1000S

1600

75

Very good

Horizon Fitness CST4.5

1000

74

Very good

Keys Fitness 320t

1200

73

Very good

Smooth Fitness 7.1HR Pro

1600

73

Very good

NordicTrack C2300

1000

70

Good

Spirit Inspire

1400

70

Very good

ProForm 750

1000

67

Good

Image 19.0 R

600

66

Good

Explanation / Answer

A. Multiple linear regression

using data analysis add in in excel.

B. Interpretation:

slope for score: for unit increase in score, price increases by $85

Intercept doesnt make sense since price cant be negative.

SUMMARY OUTPUT Regression Statistics Multiple R 0.67582 R Square 0.456733 Adjusted R Square 0.404993 Standard Error 659.6367 Observations 24 ANOVA df SS MS F Significance F Regression 2 7682052 3841026 8.8275 0.001651 Residual 21 9137531 435120.5 Total 23 16819583 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -4542.45 2221.811 -2.04448 0.053645 -9162.96 78.05863 -9162.96 78.05863 Score (points) 85.00089 28.4945 2.983063 0.007091 25.74334 144.2584 25.74334 144.2584 Quality -342.61 499.2897 -0.68619 0.500097 -1380.94 695.7198 -1380.94 695.7198
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