
Welcome to the Describing Data Numerically section of the course!
Throughout this section I will be working with several datasets that I have provided to all of you in Excel. I highly recommended that you download the "Describing Data Numerically - Blank" Excel file and follow along as you watch the videos. I specifically recommend pausing the video and trying to arrive at the same numbers I do by writing your own formulas within Excel.
To help you get started with some of the Excel formulas I have also attached a "Describing Data Numerically Excel Cheat Sheet" file that walks through a basic example of all the formulas that will be used in this section. I recommend you leverage that cheat sheet to help you as you work through this section of the course.
As always, if you want to check your work there is the "Describing Data Numerically - Answers" Excel file that is available for download.
Now, let's move onto the videos!
The data revolution is coming!
Around the globe companies are relying on data to make optimal decisions and bring about better solutions for their customers.
To stay ahead of the curve and not be left behind you need to develop data literacy - the ability to understand data and guide a data driven analysis process. By the end of this course, you will be prepared to lead a data driven project from start to finish. Data literacy will enable you to stand out among peers as you are able to drive robust data-driven decision making to your organization.
With over 20 lectures and two and a half hours of video, you will be exposed to many topics including how to collect and prepare a dataset, ways to explore data visually, how to effectively summarize a dataset with millions of rows into just a few numbers, and how to present all your results effectively at the end of a project. You will also have the opportunity to practice what we learn as you go along in the course! Downloadable Excel files will be available so students can apply the concepts as they learn them and arrive at the same results I do in each lecture.
The course is broken down into the four steps you must take when working on any data analysis project:
Collecting and Preparing Data
Exploring Data Visually
Describing Data Numerically
Telling the Story
I look forward to seeing you in the course and helping you develop data literacy!