We take the example from a presentation I made at www.dantoomeysoftware.com/Using_R_for_Marketing_Research.pptx looking at the effectiveness of different ad campaigns for grape fruit juice.
The code is as follows:
#library(s20x)
library(car)
#read the dataset from an existing .csv file
df <- read.csv("C:/Users/Dan/grapeJuice.csv",header=T)
#list the name of each variable (data column) and the first six rows of the dataset
head(df)
# basic statistics of the variables
summary(df)
#set the 1 by 2 layout plot window
par(mfrow = c(1,2))
# boxplot to check if there are outliers
boxplot(df$sales,horizontal = TRUE, xlab="sales")
# histogram to explore the data distribution shape
hist(df$sales,main="",xlab="sales",prob=T)
lines(density(df$sales),lty="dashed",lwd=2.5,col="red")
#divide the dataset into two sub dataset by ad_type
sales_ad_nature = subset(df,ad_type==0)
sales_ad_family = subset(df,ad_type==1)
#calculate the mean of sales with different ad_type
mean(sales_ad_nature$sales)
mean(sales_ad_family$sales)
#set the 1 by 2 layout plot window
par(mfrow = c(1,2))
# histogram to explore the data distribution shapes
hist(sales_ad_nature$sales,main="",xlab="sales with nature production theme ad",prob=T)
lines(density(sales_ad_nature$sales),lty="dashed",lwd=2.5,col="red")
hist(sales_ad_family$sales,main="",xlab="sales with family health caring theme ad",prob=T)
lines(density(sales_ad_family$sales),lty="dashed",lwd=2.5,col="red")
With output (several sections):
(raw data from file, first 10 rows):
|
sales |
price |
ad_type |
price_apple |
price_cookies |
|
|
1 |
222 |
9.83 |
0 |
7.36 |
8.8 |
|
2 |
201 |
9.72 |
1 |
7.43 |
9.62 |
|
3 |
247 |
10.15 |
1 |
7.66 |
8.9 |
|
4 |
169 |
10.04 |
0 |
7.57 |
10.26 |
|
5 |
317 |
8.38 |
1 |
7.33 |
9.54 |
|
6 |
227 |
9.74 |
0 |
7.51 |
9.49 |
Statistics on the data are as follows:
sales price ad_type price_apple
Min. :131.0 Min. : 8.200 Min. :0.0 Min. :7.300
1st Qu.:182.5 1st Qu.: 9.585 1st Qu.:0.0 1st Qu.:7.438
Median :204.5 Median : 9.855 Median :0.5 Median :7.580
Mean :216.7 Mean : 9.738 Mean :0.5 Mean :7.659
3rd Qu.:244.2 3rd Qu.:10.268 3rd Qu.:1.0 3rd Qu.:7.805
Max. :335.0 Max. :10.490 Max. :1.0 Max. :8.290
price_cookies
Min. : 8.790
1st Qu.: 9.190
Median : 9.515
Mean : 9.622
3rd Qu.:10.140
Max. :10.580
The data shows the effectiveness of each campaign. Family sales are more effective:
- 186.666666666667//mean of nature sales
- 246.666666666667//mean of family sales
The difference is more pronounced on the histogram displays:
