Context

The comp$-$activ database comprises activity measures of computer systems. Data was gathered from a Sun Sparcstation $20/712$ with $128$ Mbytes of memory, operating in a multi$-$user university department. Users engaged in diverse tasks, such as internet access, file editing, and CPU$-$intensive programs.

Being an aspiring data scientist, you aim to establish a linear equation for predicting 'usr' $($the percentage of time CPUs operate in user mode$).$ Your goal is to analyze various system attributes to understand their influence on the system's 'usr' mode. Problem $1-$ Define the problem and perform exploratory Data Analysis

$-$ Problem definition $-$ Check shape, Data types, statistical summary $-$ Univariate analysis $-$ Multivariate analysis $-$ Use appropriate visualizations to identify the patterns and insights $-$ Key meaningful observations on individual variables and the relationship between variables

$8$

Problem $1-$ Data Pre$-$processing

Prepare the data for modelling: $-$ Missing Value Treatment $($if needed$)-$ Outlier Detection $($treat$,$ if needed$)-$ Feature Engineering $-$ Encode the data $-$ Train$-$test split

$5$

Problem $1-$ Model Building $-$ Linear regression

$-$ Apply linear Regression using Sklearn $-$ Using Statsmodels Perform checks for significant variables using the appropriate method $-$ Create multiple models and check the performance of Predictions on Train and Test sets using Rsquare, RMSE & Adj Rsquare.

$8$

Problem $1-$ Business Insights & Recommendations

$-$ Comment on the Linear Regression