set up

Package we’re using in this analysist are as follows:

ggplot2 dplyr broom ggpubr readr

input data

After getting our packages ready, we shall input our datasets into r script and do its characteristics with looking through its summary, scatter plot, and histogram.

sales<-read.csv("C:/Users/Resha Fajri/Downloads/Stores.csv")
View(sales)
summary(sales)
##     Store.ID       Store_Area   Items_Available Daily_Customer_Count
##  Min.   :  1.0   Min.   : 775   Min.   : 932    Min.   :  10.0      
##  1st Qu.:224.8   1st Qu.:1317   1st Qu.:1576    1st Qu.: 600.0      
##  Median :448.5   Median :1477   Median :1774    Median : 780.0      
##  Mean   :448.5   Mean   :1485   Mean   :1782    Mean   : 786.4      
##  3rd Qu.:672.2   3rd Qu.:1654   3rd Qu.:1983    3rd Qu.: 970.0      
##  Max.   :896.0   Max.   :2229   Max.   :2667    Max.   :1560.0      
##   Store_Sales    
##  Min.   : 14920  
##  1st Qu.: 46530  
##  Median : 58605  
##  Mean   : 59351  
##  3rd Qu.: 71873  
##  Max.   :116320

plots

plot(Store_Sales ~ Store_Area, data = sales)

hist(sales$Store_Sales)