Use all variables and perform the following Identify the dependent (y) and independent (x1,x2,x3,x4) variables Graph the relationship between the response variable and each of explanatory variables Determine the regression equation and interpret the coefficients as well regression equation Note: Do all stepswith the help of R-Codes Data set on Sales 1 Q(Sales) Price Advert Comp. Price Income 34000 500 15 400 47.5 32500 575 10 400 47 32500 550 7.5 425 47 30000 600 12.5 400 46.5 27500 550 5 350 46 25000 600 5 325 46.5 27500 575 10 350 47 30000 550 10 425 46.5 17500 600 2.5 375 35.5 17500 625 2.5 375 35 15000 600 5 375 34.5 17500 575 2.5 350 34.5 15000 625 2.5 325 34 17500 575 2.5 375 34 15000 575 5 350 34 17500 575 2.5 400 34 27000 625 5 400 46 27500 625 12.5 350 46 27500 625 5 450 45 25000 625 5 375 44.5 30000 550 7.5 425 44.5 30000 575 12.5 425 44 27500 600 12.5 400 43.5 25000 575 10 400 43.5
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.
Use all variables and perform the following
- Identify the dependent (y) and independent (x1,x2,x3,x4) variables
- Graph the relationship between the response variable and each of explanatory variables
- Determine the regression equation and interpret the coefficients as well regression equation
Note: Do all stepswith the help of R-Codes
Data set on Sales 1
|
Q(Sales) |
Price |
Advert |
Comp. Price |
Income |
|
34000 |
500 |
15 |
400 |
47.5 |
|
32500 |
575 |
10 |
400 |
47 |
|
32500 |
550 |
7.5 |
425 |
47 |
|
30000 |
600 |
12.5 |
400 |
46.5 |
|
27500 |
550 |
5 |
350 |
46 |
|
25000 |
600 |
5 |
325 |
46.5 |
|
27500 |
575 |
10 |
350 |
47 |
|
30000 |
550 |
10 |
425 |
46.5 |
|
17500 |
600 |
2.5 |
375 |
35.5 |
|
17500 |
625 |
2.5 |
375 |
35 |
|
15000 |
600 |
5 |
375 |
34.5 |
|
17500 |
575 |
2.5 |
350 |
34.5 |
|
15000 |
625 |
2.5 |
325 |
34 |
|
17500 |
575 |
2.5 |
375 |
34 |
|
15000 |
575 |
5 |
350 |
34 |
|
17500 |
575 |
2.5 |
400 |
34 |
|
27000 |
625 |
5 |
400 |
46 |
|
27500 |
625 |
12.5 |
350 |
46 |
|
27500 |
625 |
5 |
450 |
45 |
|
25000 |
625 |
5 |
375 |
44.5 |
|
30000 |
550 |
7.5 |
425 |
44.5 |
|
30000 |
575 |
12.5 |
425 |
44 |
|
27500 |
600 |
12.5 |
400 |
43.5 |
|
25000 |
575 |
10 |
400 |
43.5 |
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