MMM_MultipleLinearRegression.Rmd

---
title: "MMM_MarketMixModeling_MultipleLinearRegression"
author: "RohitDhankar"
date: "24/05/2020"
output: pdf_document
---

This is sample code for the task being done along with Rohan Mathur = https://github.com/RohanMathur17   
https://github.com/digital-cognition-co-in/DigitalCognition/issues/24    


```{r}
library(readr)
LungCapData <- read_csv("LungCapData.csv")
attach(LungCapData)
View(LungCapData)
names(LungCapData);head(LungCapData)
#

```
     
     
For the Multiple Linear Regression that we are performing the - Dependent Variable == LungCapacity in CC  
The Multiple Independent vartiables are == Age() , Height() , Smoke() , Gender() , Caesarean()   

We fit initial Linear Regression Model with Two Independent variables == Age() and Height()     
    
    
```{r}
init_multiple_linear_m <- lm(LungCap_cc ~ Age_years + Height_inches)
#typeof(init_multiple_linear_m) # list
#class(init_multiple_linear_m) # lm - Linear Model 
summary(init_multiple_linear_m)
# the - Multiple R-squared:  0.843 -- 84.3% Variability in LUNG CAPACITY can be 
# explained by the linear relationship between - Age_years + Height_inches and LUNG CAPACITY

```
  
  
CORRELATION seen through SCATTER PLOTS    


As seen below the - Height_inches is Positivly Correlated to Lung Capacity   


```{r}
plot(LungCap_cc~Height_inches)

```


```{r}


```