Using google colab $-$ Runtime should be R coding.

Apply "Linear Regression" analysis to the IOT Dataset dataset from UCI Datasets. $($Make sure you provide an

explanation and analysis of the steps.$)$

a$.$ Install the needed packages and libraries.

b$.$ Load the dataset into Google Colab.

c$.$ EDA: Get the structure of the dataset, summarize the dataset, and display the first few and last

columns.

d$.$ Pre$-$process the dataset by finding which attributes have missing values. You can exclude or replace

the missing values to build the regression model. $($Note that the $)$ function excludes missing

value rows by default.$)$

e$.$ Apply scaling and then show the first few columns of the dataset after scaling it$.$ Link

f$.$ Divide your data into training and testing parts.

g$.$ Build the Linear Regression model based on the training part.

h$.$ Predict the result of your model based on the testing part.

i$.$ Show the difference between the actual values and predicted results

j$.$ Show the model output, summary, and visualization with your explanation.