Essential Mathematics for Data Analysis in Microsoft Excel

About This Course

Starting with the absolute basics of math and data, this course builds up your analyst skills while removing the mathematical hurdles and barriers that often come with beginning to learn how to analyze data. This course is intended for anyone with the desire to do data analysis and who would like to learn the math behind it all in a simplified way, as well as for anyone who would like a thorough refresher on the essentials.

Learn how to handle different data types, understand mathematical notation, become proficient in handling data sets and summary statistics, and even get a sneak peek into how to be effective at making stctistical inferences and predictions, all told in a way to maximize your understanding—so that afterward, you can be well on your way toward analyzing data in any field or discipline.

Please Note: Learners who successfully complete this course can earn a CloudSwyft digital certificate and skill badge - these are detailed, secure and blockchain authenticated credentials that profile the knowledge and skills you’ve acquired in this course.

Prerequisites

Basic excel proficiency

What you'll learn

In this course, you will learn how to:

Handle data sets for analysis purposes
Understand beginning mathematical notation
Work with different types of data
Summarize data with distributions and graphs
Apply summary statistics to analyze and understand data sets
Calculate business metrics and KPIs to derive business value from data sets
Apply basic inferential math to data
Use tools to forecast future trends in data

Course Staff

Ben Olsen

Sr. Content Developer

Microsoft

Ben is a Sr. Content Developer for Microsoft's Learning and Readiness team, and is an analytics professional and educator with over 8 years of industry and managerial experience. Prior to joining Microsoft, Ben ran and directed multiple consulting firms, where he also held critical analytics roles in companies as diverse as Juniper Networks, Costco, and T-Mobile. He has taught Data Visualization at The University of Washington, and recently founded Seattle Pacific University's Analytics Certificate Program.

Dr. Tom Carpenter

Assistant Professor of Psychology, Data Science consultant

Seattle Pacific University

Dr. Tom Carpenter is Assistant Professor of Psychology at Seattle Pacific University, and is also a Data Science consultant. His areas of expertise include personality-social psychology, research methods, and statistics. His teaching focuses on introductory and advanced research methods and statistics in psychology as well as social and personality psychology.

Dr. Carpenter’s research focuses on our hypocritical human nature: our propensity to ignore our overt preferences and standards and to transgress against ourselves and others. One line of research in this area focuses on implicit bias, the impulsive thoughts that can undermine our higher reasoning. Dr. Carpenter has developed new software methods for running the Implicit Association Test (IAT) using online survey software (read more here: www.iatgen.wordpress.com).

A second line of research focuses on guilt, shame, and self-forgiveness, specifically focusing on the functions of ‘guilt-proneness’ and ‘shame-proneness’ as well as associations with the general ability to forgive the self. Finally, Dr. Carpenter has conducted research related to his area of teaching (statistics education).