## Overview: # We will be taking a look at alcohol consumption (along with other variables) and its # effect on final grades in a math course....

Descriptive Analysis and Linear Regression


## Overview: # We will be taking a look at alcohol consumption (along with other variables) and its # effect on final grades in a math course. #______________________________________________________________________________________________________________ #-----Variables-----# # NOTE: See student details file to get more info on the dataset and it's variables! #______________________________________________________________________________________________________________ # TO DO: # 1 - Descriptive Analysis # - First we want to group the data by schools and gender proceed with a descriptive analysis, # comparing and contrasting the distribution of final grade in the course, # weekday alcohol consumption and weekend alcohol consumption. # You want to compare and contrast between schools (without gender concentration), # then between male & female in each school # (so look at the final grades and alcohol consumption between genders, internally, for one school... then the other...), # and lastly between genders from one school in contrast to the same gender in the other school, # - Also run correlations between weekday alcohol consumption against final grades in the course... # and weekend alcohol consumption against final grades in the course....what kind of relation exists there? # - Include any necessary visuals that supports what the data is telling us. # - In a word document, report what the raw data is telling us between the two schools and between genders, # in regards to weekday alcohol consumption, weekend alcohol consumption, and final grades. # (clearly label the sections of your work) # 2 - Linear Regression Models: # -You will be making 2 SLR models to predict Final Grades (our target variable) from the student-math.csv dataset. # The 1st model will be using weekday alcohol consumption as the only predictor. # The 2nd model will be using weekend alcohol consumption as the only predictor. # Analyze the performance of the SLR models and declare which is the best and why using the metrics we have discussed in class. # -You will also create 3 MLR models to predict Final Grades (our target variable) from the student-math.csv dataset. # The 1st model will be using both weekend alcohol consumption and weekday alcohol consumption as the only predictor # (The 1st model will be our baseline model for our next 2 models to compare against) # (The next 2 MLR models can use any number of variables except our target variable.... # Note, however, that your models should perform better than the baseline model) # Analyze the performance of the MLR models and declare which is the best and why using the metrics we have discussed in class. # - In the same word document used for the descriptive analysis, add your report for your regression models. # (clearly label the sections of your work) #______________________________________________________________________________________________________________ # packages needed (in order) #______________________________________________________________________________________________________________ # set seed ... you may use any seed #______________________________________________________________________________________________________________ ###--- Import Data ---###: df = read.csv("~/Documents/student-math.csv", header = TRUE) #______________________________________________________________________________________________________________ ###--- Factor Convert Categorical Variables ---###: ### IT WILL ALLOW YOU TO USE THOSE COLUMNS IN YOUR LINEAR REGRESSION MODELS ###