Course overview
This course is part of the “Introduction to Data Analysis with Excel” skill path, which we designed for those seeking the practical skills in Excel to perform data analysis and visualization — and ultimately help organizations make better-informed decisions. We designed it for aspiring data professionals with little experience and learners who use basic Excel in their daily jobs and want to enhance their skills.
In this course, you’ll learn why we need descriptive statistics, how to explore and apply multiple summary statistics to a spreadsheet in Excel, how to identify which statistics apply to which data type, and how to apply descriptive statistics to groups of data.
Best of all, you’ll learn by doing — you’ll practice and get feedback directly in the browser.
Key skills
- Identifying the different types of descriptive statistics
- Identifying when to use each descriptive statistic
- Applying and comparing different descriptive statistics to a single column, to multiple columns, and to groups of data
- Creating visualizations to explore and analyze data
Course outline
Exploring Data in Excel [5 lessons]
Introduction to Descriptive Statistics 1h
Lesson Objectives- Define a descriptive statistic
- Use COUNT, MIN, and MAX to describe a dataset
- Identify what datatypes can be used with AVERAGE
- Use AVERAGE to describe a few different datatype columns
Diving Deeper with Descriptive Statistics 1h
Lesson Objectives- Identify different measures of central tendency, such as the mean, median and mode
- Identify different measures of spread, such as the range, standard deviation and interquartile range
- Recognize the impact of outliers on descriptive statistics
- Identify the difference between percentiles and quartiles
- Describe the five-number summary
Applied Descriptive Statistics 1h
Lesson Objectives- Analyze multiple descriptive statistics for a single column
- Compare descriptive statistics for multiple columns and groups
- Conduct exploratory data analysis using PivotTables
Exploring Data with Data Visualization 2h
Lesson Objectives- Visualize and interpret normal, uniform, and skewed distributions
- Describe the data distributions without calculating descriptive statistics
- Create boxplots
- Interpret boxplots
Guided Project: Identifying Customers Likely to Churn for a Telecommunications Provider 1h
Lesson Objectives- Calculate descriptive statistics using Excel functions
- Use descriptive statistics to analyze real-world data
- Create PivotTables to explore differences in the data
- Compare and contrast histograms to analyze frequency distributions
- Compile a report in Excel comprised of data visualizations and tabular data
Projects in this course
Guided Project: Identifying Customers Likely to Churn for a Telecommunications Provider
In this project, we’ll conduct an Exploratory Data Analysis (EDA) on data from a telecommunications provider to create profiles on customers that are at risk of churn.
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