Project 1:

This project should be presented by group numbers 1 to 6. Dataset Cement.xlsx

contains data for concrete samples prepared using different combination of materials and their

3

corresponding compressive strength. Each component of the concrete mix is given in kg/m

and

the compressive strength in MPa. Accomplish the given tasks using this data. Hints or relevant

functions are given in parenthesis with each task.

Task 1:

Show appropriate plots (histogram, boxplots etc.) to visualize each variable and obtain

descriptive statistics for the same. (hist, plot, boxplot)

Task 2:

Plot correlation matrix to identify the dependency of compressive strength on each

variable and any possible correlations within other variables. (pairs, corrplot)

Task 3:

Create a linear multiple regression model with compressive strength of concrete as the

dependent variable and other variables as independent variables. Consider only the main effects

and ignore any interactions. Show suitable plots and important model parameters for the

regression model. (lm, plot, ggplot)

Task 4:

Rank the independent variables according to their effect on the response variable. (scale)

Task 5:

Based on the plots and model parameters, comment on the goodness of your regression

model. Suggest modifications/new models which can better predict the relationships between

compressive strength and other variables.

Task 6:

Estimate the effect of cost of each variable on the overall cost of a cubic meter concrete.

You can consider the average market cost for each variable. Based on your cost analysis, propose

the optimum proportion of each variable in a cubic meter of concrete such that the cost can be

minimized without compromising with the compressive strength.

i know you can't write the code for me or anything, but if you could give me some help on how to best start it and get a basic setup for it like a similar code or something just o I can see what I'm supposed to make that would be amazing and very helpful