Econometrics.Rmd - -title"Econometrics output pdf_document...

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--- title: "Econometrics" output: pdf_document: default html_document: df_print: paged --- Objective: To find a model that gives the most accurate relation between the target variable (Sales in our case) and some independent variables. This model is required to predict the values of target variable for the given independent variables. Defining variables: Different variables given in the data are defined in R script using the "\$" notation as given below: ```{r} sales=clothing\$sales nown=clothing\$nown nfull=clothing\$nfull npart=clothing\$npart hrsw=clothing\$hoursw floorsize=log(clothing\$ssize, exp(1)) invstshop=log(clothing\$inv1,exp(1)) invstauto=log(clothing\$inv2, exp(1)) ``` Question 1. Descriptive statistics is a statistical measure that describes or summarises features such as mean, median or quantile of variables. here we have used the following code to understand the descriptive statistics of variables under consideration: ```{r} summary(sales) summary(nown) summary(nfull) summary(npart) summary(hrsw) summary(floorsize) summary(invstshop) summary(invstauto) ``` Question 2. To find a linear regression model that could explain a satisfactory relation between target variable and other relevant independent variables, we performed a correlation test between all the variables using code as shown below: ```{r} x=cbind(sales,nown,nfull,npart,hrsw,floorsize,invstshop,invstauto) cor(x) ``` The summary of this test shows that there is strong positive co-relation between

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