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Berkeley Global
Get an overview of advanced Excel, SQL and R to perform analysis on huge sets of data. Learn the theory behind formulating statistical models using regression analysis. You also study segmentation theory and methods such as k-means clustering used for data mining and analysis.
Prerequisites:
Required
- Knowledge of math as covered in a first semester undergraduate course. Need to fulfill this prereq? Take a course in:
- Math for Management MATH X402
- Proficiency with Microsoft Excel
Course Outline
Expand or collapse section
Learning objectives:
After successfully completing this course, you will be able to:
- Understand basic statistical concepts
- Apply advanced MS Excel skills for data analysis
- Interpret data and charts from different sources
- Develop linear regression models
- Segment different sets of data
- Understand R and SQL coding
What You Learn
- Basic statistics: mean, median, variance, standard deviation
- Spreadsheets techniques: Charts, Pivots, VLOOKUP and filtering
- Segmentation methods: Cluster analysis, K-means, Bayes
- Regression: Linear, R-squared, F & T-Tests, ROC Curve
- Common data analysis tools
- SQL coding
- Introduction to R
How You Learn
- Lectures
- Analysis of case studies
- Group discussions
- Review of homework problems
- Assigned textbook chapters
- Homework assignments
Is This Course Right for You?
This course is ideal for managers, junior analysts, engineers or anyone who wants to develop the skills to comprehend huge sets of data to make informed business decisions.
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Spring enrollment opens on October 17!