# Digital Analytics & Regression

Running a 100 meter sprint in rain boots is like asking your competition to win on your behalf. Know the tools you need to have the competitive edge. Use this course as a case study to move you from problem to solution using the best suited tool set.

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.

• Learn basic concepts in statistics with step-by-step guidance on how to conduct an analysis to solve the business problem.
• Data Science is like triathlon. Programming is cycling, by far the biggest investment is required in hardware and software. Running is domain expertise and communication skills and, swimming is mathematics, statistics and modelling. There are competitions in each of these disciplines, cycling, running and swimming (and there always will be), but the need for super athletes who can do all 3 is growing. An athlete who is brilliant at one discipline can learn the other two and succeed in the triathlon.

## Course Syllabus

• Module 1 - A Case Study Approach to Analytics
3. State the hypothesis
4. Assess available data
5. Assign data for use
• Module 2 - Data Scientist Workbench
1. Using Data Scientist Workbench
2. What is R?
4. Upload a CSV data file into Data Scientist Workbench and RStudio
• Module 3 - Google Trends Data in R
1. Access Google Trends data in R
• Module 4 - Simple Linear Regression in R
1. Regression and Google Trends Data in R
2. Box Plots and Histograms in R
3. Scatter Plots & Lines of best fit in R
4. Simple Linear Regression in R
• Module 5 - Presenting Data Analytics in Business
2. Summarizing the data analytics process
3. Presenting data insights

## General Information

• This course is free.
• It is self-paced.
• It can be taken at any time.
• It can be audited as many times as you wish.

## Recommended skills prior to taking this course

• Knowledge of basic statistics is an asset
• Knowledge of basic R is an asset

• None

## Course Staff

### Fireside Analytics Inc.

Shingai Manjengwa (@Tjido) is the Director of Insights and Analytics at Fireside Analytics Inc. An NYU Stern alum, she graduated from the Stern Business Analytics Masters program in 2014 and founded Fireside Analytics the following year. Fireside Analytics is a data analytics consulting company that makes data analytics and data science skills accessible to private sector companies, non-profits and education institutions. Fireside Analytics works with clients to build their data science capabilities and train their staff and stakeholders using customized case studies. Connect with us on Facebook, Twitter and LinkedIn.