Sales of Body Price of Lens Gender Sales of Lens
155 $700 1 122
101 650 1 120
157 725 0 135
180 575 1 95
150 600 0 100
201 750 0 174
99 560 1 118
137 500 0 130
155 675 1 128
165 550 1 166
152 725 0 131
127 750 1 102
217 565 0 165
186 670 0 154
176 600 1 97
123 585 0 129
109 645 0 98
90 575 1 105
176 660 0 120
129 650 1 105
i) At the 1% level of significance, is there evidence of an overall relationship between the combination the sales of the camera body and the price of the lens and sales of the lens? Be sure that you explain in some manner the criterion or criteria you have used to arrive at your conclusion.
j) At the 1% level of significance, is there evidence of a relationship between the sales of the camera body and the sales of the lens? Be sure that you explain in some manner the criterion or criteria you have used to arrive at your conclusion.
k) At the 1% level of significance, is there evidence of a relationship between the price of the lens and the sales of the lens? Be sure that you explain in some manner the criterion or criteria you have used to arrive at your conclusion.
Using Excel, go to Data, select Data Analysis, choose Regression. Put Price of lens and Sales of Lens in X input range and Sales of Body in Y input range. Put Confidence Level as 9% (=1-0.01).
SUMMARY OUTPUT | ||||||||
Regression Statistics | ||||||||
Multiple R | 0.559 | |||||||
R Square | 0.312 | |||||||
Adjusted R Square | 0.231 | |||||||
Standard Error | 30.578 | |||||||
Observations | 20 | |||||||
ANOVA | ||||||||
df | SS | MS | F | Significance F | ||||
Regression | 2 | 7210.948 | 3605.474 | 3.856 | 0.042 | |||
Residual | 17 | 15894.802 | 934.988 | |||||
Total | 19 | 23105.750 | ||||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 99.0% | Upper 99.0% | |
Intercept | 22.155 | 69.410 | 0.319 | 0.753 | -124.288 | 168.598 | -179.012 | 223.322 |
Price of Lens | 0.047 | 0.098 | 0.484 | 0.635 | -0.159 | 0.253 | -0.236 | 0.330 |
Sales of Lens | 0.779 | 0.290 | 2.684 | 0.016 | 0.167 | 1.391 | -0.062 | 1.620 |
i) H0: β1 = β2 = 0, There is no evidence of an overall relationship between the combination of sales of the camera body and the price of the lens and sales of the lens
H1: At least one of βi ≠ 0, There is no evidence of an overall relationship between the combination of sales of the camera body and the price of the lens and sales of the lens
p-value (Significance F) = 0.042
Level of significance = 0.01
Since p-value is more than 0.01, we do not reject the null hypothesis.
So, there is no evidence of an overall relationship between the combination of sales of the camera body and the price of the lens and sales of the lens.
j) H0: β2 = 0, There is no evidence of an overall relationship between the sales of the camera body and sales of the lens
H1: β2 ≠ 0, There is no evidence of an overall relationship between the sales of the camera body and sales of the lens
p-value (Sales of Lens) = 0.635
Level of significance = 0.01
Since p-value is more than 0.01, we do not reject the null hypothesis.
So, there is no evidence of an overall relationship between the the sales of the camera body and sales of the lens.
k) H0: β1 = 0, There is no evidence of an overall relationship between the sales of the camera body and price of the lens
H1: β1 ≠ 0, There is no evidence of an overall relationship between the sales of the camera body and price of the lens
p-value (Price of Lens) = 0.167
Level of significance = 0.01
Since p-value is more than 0.01, we do not reject the null hypothesis.
So, there is no evidence of an overall relationship between the the sales of the camera body and price of the lens.
Sales of Body Price of Lens Gender Sales of Lens 155 $700 1 122 101 650 1 120 157 725 0 135 180 575 1 95 150 600 0 100 201 750 0 174 99 560 1 118 137 500 0 130 155 675 1 128 165 550 1 166 ...
Sales of Body Price of Lens Gender Sales of Lens 155 $700 1 122 101 650 1 120 157 725 0 135 180 575 1 95 150 600 0 100 201 750 0 174 99 560 1 118 137 500 0 130 155 675 1 128 165 550 1 166 ...
Sales of Body Price of Lens Gender Sales of Lens 155 $700 1 122 101 650 1 120 157 725 0 135 180 575 1 95 150 600 0 100 201 750 0 174 99 560 1 118 137 500 0 130 155 675 1 128 165 550 1 166 152 725 0 131 127 750 1 102 217 565 0 165 186 670 0 154 176 600 1 97 123 585 0 129 109 645 0 98 90 575...
Sales of Body Price of Lens Gender Sales of Lens 155 $700 1 122 101 650 1 120 157 725 0 135 180 575 1 95 150 600 0 100 201 750 0 174 99 560 1 118 137 500 0 130 155 675 1 128 165 550 1 166 152 725 0 131 127 750 1 102 217 565 0 165 186 670 0 154 176 600 1 97 123 585 0 129 109 645 0 98 90 575...
PLEASE IF POSSIBLE USE PH STAT Sales of Body Price of Lens Gender Sales of Lens 155 $700 1 122 101 650 1 120 157 725 0 135 180 575 1 95 150 600 0 100 201 750 0 174 99 560 1 118 137 500 0 130 155 675 1 128 165 550 1 166 152 725 0 131 127 750 1 102 217 565 0 165 186 670 0 154 176 600 1 97 123 585 0 129...
sales of body price of lens gender sales of lens 155 700 1 122 101 650 1 120 157 725 0 135 180 575 1 95 150 600 0 100 201 750 0 174 99 560 1 118 137 500 0 130 155 675 1 128 165 550 1 166 152 725 0 131 127 750 1 102 217 565 0 165 186 670 0 154 176 600 1 97 123 585 0 129 109 645 0 98 90...
Sales of Body Price of Lens Gender Sales of Lens 155 $700 1 122 101 650 1 120 157 725 0 135 180 575 1 95 150 600 0 100 201 750 0 174 99 560 1 118 137 500 0 130 155 675 1 128 165 550 1 166 152 725 0 131 127 750 1 102 217 565 0 165 186 670 0 154 176 600 1 97 123 585 0 129 109 645 0 98 90 575...
For this problem, you will add another independent variable, the variable “gender” to the data. In this case the variable is set to 0 if the purchaser of the camera body is a male and set to 1 if the purchaser of the camera body is not a male (is a female). Rerun the regression model using three independent variables, sales of the camera body (x1), price of the lens (x2) and gender (x3). The dependent variable is still number...
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