ASSIGNMENT $3$

Write a code that contains the answers of the questions given below and save your file by using your

name "Name.R$".$ Send me the $.$R file.

Add a comment line that contains your name, surname, student ID and department.

Draw a Box$-$and$-$Whisker Plot by using iris dataset $($Petal length vs Species$).$

Show the box$-$plot of each species at the same plot.

Label $x$ and $y$ axes. Give a title to the chart.

Show all the necessary information to build the box plots in a list.

Save your plot by using appropriate codes. The name of the file will be "Name$-$BoxPlot.png$"($i$.$e$.,$

Seza$-$BoxPlot.png$).$ Width and height of the chart should be $800$ and $600,$ respectively.

Draw a Histogram by using iris dataset $($Frequency vs$.$ Petal length$).$

Set the color of the histogram as red.

Label $x$ and $y$ axes. Give a title to the chart.

Show all the necessary information to build the histogram in a list.

Save your plot by using appropriate codes. The name of the file will be "Name$-$Histogram.png$"($i$.$e$.,$

Seza$-$Histogram.png$).$ Width and beight of the chart should be $800$ and $600,$ respectively.

Create a dataframe called Name.Iris $($i$.$e$.,$ Seza.Iris$)$ by assigning all the content in the iris dataset.

Create a file called "Name.csv$"($i$.$e$.,$ Seza.csv$)$ by using "write.csv$"$ command. The fill should contain

the data frame you created.

Use "Read.csv$"$ command to assign the data in the "Name.csv$"$ file to a dataframe named "Name".

Use str$()$ command to check the structure of the "Name" dataframe.

Use summary$()$ command to check the descriptive statistics of the "Name" dataframe.

Create education and test sets by using iris data set.

Use set seed$()$ command to generate the same random numbers.

The sample size of the test set will be $25.$ The remaining data will be at the education set.

The name of the test set will be "Name.test" $($i$.$e$.,$ Seza.test$).$

The name of the education set will be "Name.education" $($i$.$e$.,$ Seza.education$).$

Create a linear model by using iris data set.

Dependent variable will be Sepal Length.

All the other variables will be independent variables.

The name of the model will be Name.model$1($i$.$e$.,$ Seza.model$1).$

Show the summary of the model.

Create a linear model by using iris data set.

Dependent variable will be Sepal Length.

All the other variables $($except species$)$ will be independent variables.

The name of the model will be Name.model$2($i$.$e$.,$ Seza.model$2).$

Show the summary of the model.

Create a linear model by using iris data set.

Dependent variable will be Sepal Length. Sepal Width will be the independent variable.

The name of the model will be Name.model$3($i$.$e$.,$ Seza.model$3).$

Show the summary of the model.