Task

Demonstrate understanding and application of basic statistical techniques using the R language that meets the specifications described in the case study.

Description

Create a case study that utilises R language to perform basic statistical analysis on a publicly available dataset as described in the case study below.

Case Study:

Step $1$: Dataset Selection: Choose a suitable dataset from publicly available datasets commonly used with R$.$ Some popular options include:

$$mtcars$$: This dataset contains information about various car models, including variables such as horsepower, miles per gallon $($MPG$),$ and number of cylinders.

$$iris$$: This dataset includes measurements of different iris flower species, including variables like petal length, petal width, and sepal length.

$$diamonds$$: This dataset contains information about diamonds, including variables such as carat weight, cut quality, and price.

Step $2$: Data Import: Import the chosen dataset into R using appropriate functions or libraries. Make sure to include the necessary code for dataset importation in your submission.

Step $3$: Data exploration: Perform data exploration by examining the structure, summary statistics, and basic visualisation of the dataset. This step should involve techniques covered in the earlier weeks $($Weeks $1,2,$and $3)$ of the subject.

Step $4$: Descriptive Statistics: Calculate and present descriptive statistics, including measures of central tendency $($mean$,$ median, mode$)$ and measures of dispersion $($variance$,$ standard deviation, range$)$ for relevant variables in the dataset.

Step $5$: R Code Documentation: Document your R code using comments to explain the purpose and functionality of each step in the analysis. Make sure your code is well$-$structured and easily understandable.