Digital Analytics & Regression
Follow a case study where you define the business objective, establish the data required to address that objective, and use R, the programming language, to derive insights from the data. As with any business challenge, you will be required to articulate your findings to a business audience.
Duration: 10hrs
Course Content:
- Module 1 - A Case Study Approach to Analytics
- Understand the business context
- Formulate the business objective
- State the hypothesis
- Assess available data
- Assign data for use
- Module 2 - Data Scientist Workbench
- Using Data Scientist Workbench
- What is R?
- Loading data into R with Data Scientist Workbench
- Upload a CSV data file into Data Scientist Workbench and RStudio
- Module 3 - Google Trends Data in R
- Access Google Trends data in R
- Module 4 - Simple Linear Regression in R
- Regression and Google Trends Data in R
- Box Plots and Histograms in R
- Scatter Plots & Lines of best fit in R
- Simple Linear Regression in R
- Module 5 - Presenting Data Analytics in Business
- Using data to answer a business question
- Summarizing the data analytics process
- Presenting data insights