A. At 95% confidence, determine which variables are significant and which are not. B. Remove any independent variable that is not significant from the estimate regression equation. What is your recommended estimated regression equation? Compute the R2 with the value of R2 from part (a). Discuss the differences.
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.
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4. The prices of Rawlston, Inc. stock (y) over a period of 12 days, the number of shares (in 100s) of
company's stocks sold (x1), and the volume of exchange (in millions) on the New York Stock
Exchange (x2) are shown below.
Day
(v)
87.50
(x1)
(x2)
11.00
950
86.00
945
11.25
3
84.00
940
11.75
4.
83.00
930
11.75
84.50
935
12.00
6.
84.00
935
13.00
82.00
80.00
932
13.25
14.50
8.
938
9.
78.50
925
15.00
10
79.00
900
16.50
11
77.00
875
17.00
12
77.50
870
17.50
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