## Simple Linear Regression Assignment Case Solution

**Question 3**

A histogram has been created in the excel spreadsheet for the response variable. It could be seen that it forms half of the bell shaped curve, which shows that the regression assumption has been met in the linear regression model.

**Focus Questions**

**Question 1**

Simple linear or multiple regression analysis is performed in statistics in order to determine the relationship between the dependent or the scalar variable and one or more independent or explanatory variables. The ANOVA table shows the level of the significance of the dependency between the independent and the dependent variables.

Question 2

In order to develop a regression model, first of all the relevant data is collected through primary or secondary sources for all the independent and the dependent variable. All those independent variables that are deemed to have a relationship or impact upon the dependent variables are incorporated in the model and a final model is formulated.

**Question 3**

The estimated regression coefficients tell the volatility or the variance in the dependent variable as a result of the particular independent variable. The beta parameters tell us that whether that variation or dependency is significant or not.

**Question 4**

The quality of regression models could be assessed through many ways, however, the two most important are the confidence intervals and the adjusted r square values. For the regression model to be static and valid, the confidence intervals need to be much smaller as compared to the parameter values. On the other hand, if the value of the adjusted r square is close to 1 then it is considered that the model is fit and the quality of regression is high. Other method is the use of the residual plot which shows the difference between the measured and the calculated values.

**Question 5**

**The 4 underlying assumptions of the regression model include:**

1). The dependent and the independent variables should be measured at ratio or interval which means at the continuous level. This could be checked by looking at the data set.

2). Second, there should be a linear relationship between all the variables. This could be checked through a scatter plot by plotting the dependent variable against the independent variable.

3). There should be no outliers in the data set. This could also be checked through the scatter plot.

4). The fourth assumption of the regression is that the residuals of the regression variables are normally distributed. This could be checked by creating a histogram to check whether regression line is normally distributed or not………………..

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