Using the attached dataset, perform a multiple regression test/analysis of life expectancy in relation to country, and BMI.
Use the steps below as a guide. The deliverable will be R file with code, and a report of findings.
• Split the data into training and test sets, with the test set including at least the last 12 months of data.
• First develop a simple time series regression model with just one predictor and one forecast variable using the training data.
• Second, create another model where you will include trend and seasonality in your model as dummy variables
• If you have more predictor variables available, include them, and create a third model.
• Draw charts showing the relationship between the variables (hint: correlation, ggpairs() etc.)
• For each model, create regression summary report, explore the model coefficients and interpret them. Talk about the significant variables and why do you think they make business sense to be significant.
• For each model, plot the actual data for all years against the forecast with forecast intervals (80% and 95% confidence). What recommendation/conclusions can you draw based on your plots?
• For each model, report residual diagnostics. What can you conclude from the residual diagnostics? Do your model residuals have serial correlation? If so, what does this mean?
• For each model, report the accuracy in forecasting the test data. How accurate are your models and which model is most accurate?
Prepare a business document with executive summary, description of the dataset, description of the variables, their relationships with each other, model selection, significant parameters, and final conclusion.
Provide nicely formatted charts and graphs.
Provide all R-codes as an appendix with clear labeling/comments so that it is easy to figure out which section of the report used which R code.
I'm computer engineering TA with 10+ years of experience.
Experienced with data structures and algorithms , computation theory , discrete math
Experienced with R and python programming
Experienced with big data analytics , machine learning - logistic and linear regression
through python 2.7 and 3.6
Developed megaprojects using R , recently complete machine learning Matches results prediction
Will provide you fully commented code + any required documentations
I am a professor of statistics and mathematics and I can surely help you with the task as I am an expert in R programming. I can even comment on the code for you to understand. I have checked the dataset and can get the work done.
I am a preferred freelancer here. You can check sample work I have done in my portfolio and my profile reviews: https://www.freelancer.com/u/freelancerpr0?w=f
Please come over chat and let's discuss the topics and the goals. I can surely help you with this task. Looking forward to working with you.