Statistics and Data Analysis with Excel: Essentials

Statistics and Data Analysis with Excel: Essentials

This course is part of Statistics and Data Analysis with Excel Specialization

Instructor: Assoc Prof Prashan S. M. Karunaratne

Access provided by Capgemini

6,470 already enrolled

5 modules

Gain insight into a topic and learn the fundamentals.

64 reviews

Beginner level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

5 modules

Gain insight into a topic and learn the fundamentals.

64 reviews

Beginner level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Evaluate the impact of statistical methods on organisation-wide decision-making processes.
Design spreadsheet models to predict organisational trends and outcomes.
Critically interpret graphical data representations to identify actionable insights.
Formulate data analysis strategies to optimise organisational performance.

Skills you'll gain

Tools you'll learn

Microsoft Excel

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

9 assignments

Taught in English

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Build your subject-matter expertise

This course is part of the Statistics and Data Analysis with Excel Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 5 modules in this course

Statistics and data analysis involve collecting, analysing, interpreting and presenting data to stakeholders to enhance their decision-making.

Statistics is all about making sense of numbers and finding patterns in the data - in business, health, sports, science, the arts, and more. Statistics can be divided into two main branches, descriptive statistics and inferential statistics. Descriptive Statistics summarise and describe the features of a data set. Inferential Statistics allow us to make predictions or inferences about a population based on a sample of data that we have access to. In this course, you will be equipped with the tools and techniques to transform your data into meaningful output to drive insights for your work and your organisation. We will explore both Descriptive Statistics as well as Inferential Statistics.

In this module, we will cover the Introduction to Statistics. What is Statistics? What are the different types of Statistics? How do we summarise large volumes of data to make it more meaningful to generate insights for our organisation? Welcome to the Introduction to Statistics!

What's included

5 videos9 readings2 assignments

5 videos Total 17 minutes

Welcome to Statistics and Data Analysis with Excel: Essentials 2 minutes
Introduction to Statistics and Measures of Centredness 4 minutes
Descriptive Statistics - Measures of Centredness 4 minutes
Formulas for Measures of Centredness 2 minutes
Histograms 5 minutes

9 readings Total 90 minutes

Course Information 10 minutes
Your Learning Path - How the course is structured 10 minutes
Download the workbooks 10 minutes
At the end of this module - your final Excel file should look like this 10 minutes
Toolbox Summary - Introduction to Data and Analytics 10 minutes
Toolbox Summary - Statistics and Analytics Terminology 10 minutes
Toolbox Summary - Descriptive Statistics 10 minutes
Why the Practice Assignment is after the Graded Assignment 10 minutes
Optional Reading - Introduction to Statistics 10 minutes

2 assignments Total 60 minutes

Test Yourself: Introduction to Statistics 30 minutes
Introduction to Statistics - Practice for Final Assignment 30 minutes

In this module, we will cover Variance. Now that we know how to measure centred-ness, how do we measure spread? What are the various numerical and graphical measures of spread? Why is measuring spread important? Welcome to Variance!

What's included

4 videos6 readings2 assignments

4 videos Total 16 minutes

Measures of Spread 5 minutes
Descriptive Statistics - Measures of Spread 3 minutes
Formulas for Measures of Spread 4 minutes
Boxplots 5 minutes

6 readings Total 60 minutes

Download the Workbooks 10 minutes
At the end of this module - your final Excel file should look like this 10 minutes
Toolbox Summary - Summarising Data 10 minutes
Toolbox Summary - Variance and Spread 10 minutes
Why the Practice Assignment is after the Graded Assignment 10 minutes
Optional Reading - Variance 10 minutes

2 assignments Total 60 minutes

Test Yourself: Variance 30 minutes
Variance - Practice for Final Assignment 30 minutes

Now that we have looked at measures of centred-ness and measures of spread, let's bring it all together. What do data distributions look like? What can we infer from a sample of data if we know its centre and its spread? Are all distributions the same? Welcome to the Normal Distribution!

What's included

4 videos6 readings2 assignments

4 videos Total 17 minutes

The Normal Distribution 3 minutes
Normal Distribution and Excel 6 minutes
Standard Normal Distribution and the Central Limit Theorem 5 minutes
Z statistics versus t statistics 2 minutes

6 readings Total 60 minutes

Download workbooks on Normal Distribution 10 minutes
At the end of this module - your final Excel file should look like this 10 minutes
Toolbox Summary - The Normal Distribution 10 minutes
Toolbox Summary - The Central Limit Theorem 10 minutes
Why the Practice Assignment is after the Graded Assignment 10 minutes
Optional Reading - The Normal Distribution 10 minutes

2 assignments Total 60 minutes

Test Yourself: Normal Distribution 30 minutes
Normal Distribution - Practice for Final Assignment 30 minutes

Now that you have mastered the Normal Distribution, let's do some testing! What if you want to make an inference about an entire population but you only have a sample of data? How can you use the statistics of a sample to make decisions for your organisation? How large should your sample size be? Welcome to Statistical Inference!

What's included

4 videos8 readings3 assignments

4 videos Total 20 minutes

Statistical Inference 5 minutes
Steps of Hypothesis Testing 6 minutes
Z-test for a One Sample Hypothesis Test 6 minutes
t-test for a One Sample Hypothesis Test 4 minutes

8 readings Total 80 minutes

Download the Module 5 Workbooks 10 minutes
At the end of this module - your final Excel file should look like this 10 minutes
Toolbox Summary - Statistical Inference 10 minutes
Toolbox Summary - Hypothesis Testing 10 minutes
Hypothesis Testing for One Sample Tests 10 minutes
Why the Practice Assignment is after the Graded Assignment 10 minutes
Optional Reading - Statistical Inference 10 minutes
Summary of the Course and Next Steps 10 minutes

3 assignments Total 90 minutes

Test Yourself: Statistical Inference 30 minutes
Final Assignment - Excel Skills for Statistics and Data Analysis: Essentials 30 minutes
Statistical Inference - Practice for Final Assignment 30 minutes

The material in this module consists of a series of Toolboxes. While the material covered in these Toolboxes is not necessarily related to Statistics - these Toolboxes will help you expand your tools and techniques in Microsoft Excel. To further your skills in Microsoft Excel in domains beyond Statistics, you may want to consider our other courses and specializations: Excel Skills for Business. Excel Skills for Data Analytics and Visualization, Excel Skills for Business Forecasting