B$.$ Section B$-$R

Write all your commands in one script file that you should save as "Script.R$"$

Capture the collected data in the form of a data frame with a name of your choice

For the data frame that you created above,

$($a$)$ Write an R command to extract the element in the $8^{th}$ row $4^{th}$ column.

$($b$)$ Write an R command to extract the ${15}^{th}$ row.

$($c$)$ Write an R command to extract the ${11}^{th}$ column.

$($d$)$ Write an R command to extract the elements in rows $2,1,19$ columns $2$ to $7$

$($e$)$ Write an R command to extract all people who like the BMW$.$

$($f$)$ Write an R command to extract data on all the female respondents who like the BMW$.$

$($g$)$ Write an R command to extract the data for all respondents who do not have Postgraduate degrees.

$($h$)$ Write an R command to extract the data for all respondents who BMW or Mercedes Benz..

$($i$)$ Add a new variable called heightcat and created by dividing the heights into $3$ equal categories named "short","Medium" and "tall".

$($j$)$ Write an R command to extract respondents whose height is below $130$ cm $.$

$($k$)$ Sort your data frame in descending order of height.

$($l$)$ Export your data frame to the file "final.csv$"$

$($m$)$ Create a histogram of the heights of these individuals. Comment on the histogram.

$($n$)$ Create a well labeled bar graph to depict the distribution of the car prefences of the respondents. Label the axis, and give a title to the bar graph. Comment on the bar graph.

$($o$)$ Perform a chi$-$squared test to determine if the heightcat is independent of gender? Comment on the results of the chi$-$square test