Determine if you should accept or reject the null hypothesis if the alpha value was 0.05. Write down the resultant regression equation. SUMMARY OUTPUT Regression Statistics Multiple R 0.929366 R Square 0.863722 Adjusted R Square 0.846687 Standard Error 0.608552 Observations 10 ANOVA df SS MS F Significance F Regression 1 18.77731 18.77731 50.7035 9.99E-05 Residual 8 2.962685 0.370336 Total 9 21.74 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 19.33123 0.505861 38.21448 2.41E-10 18.16471 20.49774 18.16471 20.49774 X Variable 1 -0.0006 8.43E-05 -7.12064 9.99E-05 -0.00079 -0.00041 -0.00079 -0.00041 The base information is: Brand Weight Price FELT F5 17.8 2100 PINARELLO Paris 16.1 6250 ORBEA Orca GDR 14.9 8370 EDDY MERCKX EMX-7 15.9 6200 BH RC1 Ultegra 17.2 4000 BH Ultralight 386 13.1 8600 CERVELO S5 Team 16.2 6000 GIANT TCR Advanced 2 17.1 2580 WILIER TRIESTINA Gran Turismo 17.6 3400 SPECIALIZED S-Works Amira SL4 14.1 8000
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Determine if you should accept or reject the null hypothesis if the alpha value was 0.05. Write down the resultant regression equation.
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SUMMARY OUTPUT |
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Regression Statistics |
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Multiple R |
0.929366 |
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R Square |
0.863722 |
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Adjusted R Square |
0.846687 |
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Standard Error |
0.608552 |
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Observations |
10 |
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ANOVA |
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df |
SS |
MS |
F |
Significance F |
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Regression |
1 |
18.77731 |
18.77731 |
50.7035 |
9.99E-05 |
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Residual |
8 |
2.962685 |
0.370336 |
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Total |
9 |
21.74 |
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|
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Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
Lower 95.0% |
Upper 95.0% |
|
Intercept |
19.33123 |
0.505861 |
38.21448 |
2.41E-10 |
18.16471 |
20.49774 |
18.16471 |
20.49774 |
|
X Variable 1 |
-0.0006 |
8.43E-05 |
-7.12064 |
9.99E-05 |
-0.00079 |
-0.00041 |
-0.00079 |
-0.00041 |
The base information is:
|
Brand |
Weight |
Price |
|
FELT F5 |
17.8 |
2100 |
|
PINARELLO Paris |
16.1 |
6250 |
|
ORBEA Orca GDR |
14.9 |
8370 |
|
EDDY MERCKX EMX-7 |
15.9 |
6200 |
|
BH RC1 Ultegra |
17.2 |
4000 |
|
BH Ultralight 386 |
13.1 |
8600 |
|
CERVELO S5 Team |
16.2 |
6000 |
|
GIANT TCR Advanced 2 |
17.1 |
2580 |
|
WILIER TRIESTINA Gran Turismo |
17.6 |
3400 |
|
SPECIALIZED S-Works Amira SL4 |
14.1 |
8000 |
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