# Clear the workspace
  rm(list = ls()) # Clear environment
  gc()            # Clear unused memory
##          used (Mb) gc trigger (Mb) max used (Mb)
## Ncells 521432 27.9    1159612   62   660385 35.3
## Vcells 947692  7.3    8388608   64  1769723 13.6
  cat("\f")       # Clear the console
  1. What is correlation ?

Correlation is a statistical measure that indicates the extent to which two or more variables fluctuate in relation to each other.

A positive correlation indicates the extent to which those variables increase or decrease in parallel.

A negative correlation indicates the extent to which one variable increases as the other decreases.

  1. What is covariance ?

Covariance in statistics measures the extent to which two variables vary linearly. It reveals whether two variables move in the same or opposite directions.

A positive covariance means asset returns move together.

A negative covariance means they move inversely.

library(readr)

setwd("C:/Users/LENOVO/Downloads/Data Analytics/Week_12")

#Load the data
Prod = read.csv("products.csv")

Invent = read.csv("inventory.csv")
library(visdat)
## Warning: package 'visdat' was built under R version 4.3.2
vis_dat(Prod)

vis_dat(Invent)

#Merge Chapter and Dialogue

Merged = merge(x = Prod,
             y = Invent,
             by = c("Product_ID"))

vis_dat(Merged)

library(stargazer)
## 
## Please cite as:
##  Hlavac, Marek (2022). stargazer: Well-Formatted Regression and Summary Statistics Tables.
##  R package version 5.2.3. https://CRAN.R-project.org/package=stargazer
stargazer(Merged, 
          type = "text", 
          title = "Summary")
## 
## Summary
## ===========================================
## Statistic       N    Mean  St. Dev. Min Max
## -------------------------------------------
## Product_ID    1,593 18.073  10.064   1  35 
## Store_ID      1,593 25.326  14.478   1  50 
## Stock_On_Hand 1,593 18.670  18.998   0  139
## -------------------------------------------
summary(Merged)
##    Product_ID    Product_Name       Product_Category   Product_Cost      
##  Min.   : 1.00   Length:1593        Length:1593        Length:1593       
##  1st Qu.: 9.00   Class :character   Class :character   Class :character  
##  Median :18.00   Mode  :character   Mode  :character   Mode  :character  
##  Mean   :18.07                                                           
##  3rd Qu.:27.00                                                           
##  Max.   :35.00                                                           
##  Product_Price         Store_ID     Stock_On_Hand   
##  Length:1593        Min.   : 1.00   Min.   :  0.00  
##  Class :character   1st Qu.:13.00   1st Qu.:  6.00  
##  Mode  :character   Median :25.00   Median : 13.00  
##                     Mean   :25.33   Mean   : 18.67  
##                     3rd Qu.:38.00   3rd Qu.: 24.00  
##                     Max.   :50.00   Max.   :139.00
correlation = cor(Merged$Store_ID,
                  Merged$Stock_On_Hand,
                  use = "complete.obs")

correlation
## [1] 0.0704017
covariance = cov(Merged$Store_ID,
                  Merged$Stock_On_Hand,
                  use = "complete.obs")
covariance
## [1] 19.3633