Executive Summary

Our company recently measured the iris flower and gert iris dataset. We would like to know more of the data.

Introduction

Our company recently measured the iris flower and gert iris dataset. We would like to know more of the data. - How are the variables correlated to each other? - What is the distribution of each variable?

Data Source

Our company recently measured the iris flower and gert iris dataset

Key Findings

Summary Statistics

## Warning: package 'pander' was built under R version 4.5.3
## Warning: package 'broom' was built under R version 4.5.3
## 
## First 6 rows
##   sepal.length sepal.width petal.length petal.width variety
## 1          5.1         3.5          1.4         0.2  Setosa
## 2          4.9         3.0          1.4         0.2  Setosa
## 3          4.7         3.2          1.3         0.2  Setosa
## 4          4.6         3.1          1.5         0.2  Setosa
## 5          5.0         3.6          1.4         0.2  Setosa
## 6          5.4         3.9          1.7         0.4  Setosa
## 
## Structure
## 'data.frame':    149 obs. of  5 variables:
##  $ sepal.length: num  5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
##  $ sepal.width : num  3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
##  $ petal.length: num  1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
##  $ petal.width : num  0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
##  $ variety     : chr  "Setosa" "Setosa" "Setosa" "Setosa" ...
## 
## Summary Statistics
sepal.length sepal.width petal.length petal.width variety
Min. :4.300 Min. :2.00 Min. :1.000 Min. :0.100 Length:149
1st Qu.:5.100 1st Qu.:2.80 1st Qu.:1.600 1st Qu.:0.300 Class :character
Median :5.800 Median :3.00 Median :4.300 Median :1.300 Mode :character
Mean :5.844 Mean :3.06 Mean :3.749 Mean :1.195 NA
3rd Qu.:6.400 3rd Qu.:3.30 3rd Qu.:5.100 3rd Qu.:1.800 NA
Max. :7.900 Max. :4.40 Max. :6.900 Max. :2.500 NA

What is the distribution of each variable?

Normality Test of Sepal Width
## 
## ---------------
## Variable: sepal.width
## ---------------
## 
## Normality Test
statistic p.value method
0.985 0.1062 Shapiro-Wilk normality test

If P-Value < 0.05, we can reject null h0. The variable is not normally distrbuted. If more than 0.05, it is normally distributed.

Normality Test of Sepal Length
## 
## ---------------
## Variable: sepal.length
## ---------------
## 
## Normality Test
statistic p.value method
0.9756 0.009234 Shapiro-Wilk normality test

If P-Value < 0.05, we can reject null h0. The variable is not normally distrbuted. If more than 0.05, it is normally distributed.

Normality Test of Petal Width
## 
## ---------------
## Variable: petal.width
## ---------------
## 
## Normality Test
statistic p.value method
0.9019 1.853e-08 Shapiro-Wilk normality test

If P-Value < 0.05, we can reject null h0. The variable is not normally distrbuted. If more than 0.05, it is normally distributed.

Normality Test of Petal length
## 
## ---------------
## Variable: petal.length
## ---------------
## 
## Normality Test
statistic p.value method
0.8768 8.635e-10 Shapiro-Wilk normality test

If P-Value < 0.05, we can reject null h0. The variable is not normally distrbuted. If more than 0.05, it is normally distributed.

How are the variables correlated to each other?

Correlation Matrix
## 
## 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
##              sepal.length sepal.width petal.length petal.width
## sepal.length    1.0000000  -0.1181293    0.8737381   0.8206195
## sepal.width    -0.1181293   1.0000000   -0.4260283  -0.3628942
## petal.length    0.8737381  -0.4260283    1.0000000   0.9627723
## petal.width     0.8206195  -0.3628942    0.9627723   1.0000000
Correlation Test of Petal length Petal Width
## 
## Pearson
## [1] 0.9627723
## 
## Spearman
## [1] 0.9376545
## 
## Kendall
## [1] 0.8065882
Table continues below
estimate statistic p.value parameter conf.low conf.high
0.9628 43.18 2.082e-85 147 0.9489 0.9729
method alternative
Pearson’s product-moment correlation two.sided

We can infer…

Correlation Test of Sepal length Sepal Width
## 
## Pearson
## [1] -0.1181293
## 
## Spearman
## [1] -0.1681023
## 
## Kendall
## [1] -0.0786184
Table continues below
estimate statistic p.value parameter conf.low conf.high
-0.1181 -1.442 0.1513 147 -0.2737 0.0435
method alternative
Pearson’s product-moment correlation two.sided

We can infer….

Conclusion

Conclusions