What career opportunities does this course support?

<text variant="body1">Statistical literacy is a valued skill across a wide range of roles — including data analyst, business analyst, research assistant, operations manager, HR professional, financial analyst, and healthcare administrator. This course builds the foundational skills that underpin data-informed decision-making in any of these fields.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Statistics and Data Analysis with Excel: Essentials

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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

9,687 already enrolled

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5 modules

Gain insight into a topic and learn the fundamentals.

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.

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

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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

Data drives decisions in every field — business, health, science, sports, and beyond. This course gives you the statistical tools to make sense of data, spot patterns, and present findings that inform real-world decisions.

You'll work through both branches of statistics in a structured, practical sequence. Descriptive statistics help you summarise and describe data — covering measures of centredness like mean, median, and mode, and measures of spread including variance, standard deviation, and boxplots. You'll then move to inferential statistics, where you'll use the normal distribution, the Central Limit Theorem, and hypothesis testing to draw conclusions about whole populations from sample data. Everything is applied in Microsoft Excel, so you're not just learning theory — you're building working spreadsheet models. Each module includes downloadable workbooks, toolbox summary references, and both practice and graded assignments to reinforce your skills step by step. The course closes with a final assignment that brings all four modules together, giving you the opportunity to demonstrate your full range of statistical and analytical skills in a single integrated Excel model. Who this is for: Students, business professionals, and anyone who works with data and wants to understand it more rigorously. No prior statistics or Excel expertise is required.

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 videosTotal 17 minutes

Welcome to Statistics and Data Analysis with Excel: Essentials2 minutes
Introduction to Statistics and Measures of Centredness4 minutes
Descriptive Statistics - Measures of Centredness4 minutes
Formulas for Measures of Centredness2 minutes
Histograms5 minutes

9 readingsTotal 90 minutes

Course Information10 minutes
Your Learning Path - How the course is structured10 minutes
Download the workbooks10 minutes
At the end of this module - your final Excel file should look like this10 minutes
Toolbox Summary - Introduction to Data and Analytics10 minutes
Toolbox Summary - Statistics and Analytics Terminology10 minutes
Toolbox Summary - Descriptive Statistics10 minutes
Why the Practice Assignment is after the Graded Assignment10 minutes
Optional Reading - Introduction to Statistics10 minutes

2 assignmentsTotal 60 minutes

Introduction to Statistics - Practice for Final Assignment30 minutes
Test Yourself: Introduction to Statistics30 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 videosTotal 16 minutes

Measures of Spread5 minutes
Descriptive Statistics - Measures of Spread3 minutes
Formulas for Measures of Spread4 minutes
Boxplots5 minutes

6 readingsTotal 60 minutes

Download the Workbooks10 minutes
At the end of this module - your final Excel file should look like this10 minutes
Toolbox Summary - Summarising Data10 minutes
Toolbox Summary - Variance and Spread10 minutes
Why the Practice Assignment is after the Graded Assignment10 minutes
Optional Reading - Variance10 minutes

2 assignmentsTotal 60 minutes

Variance - Practice for Final Assignment30 minutes
Test Yourself: Variance30 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 videosTotal 17 minutes

The Normal Distribution3 minutes
Normal Distribution and Excel6 minutes
Standard Normal Distribution and the Central Limit Theorem5 minutes
Z statistics versus t statistics2 minutes

6 readingsTotal 60 minutes

Download workbooks on Normal Distribution10 minutes
At the end of this module - your final Excel file should look like this10 minutes
Toolbox Summary - The Normal Distribution10 minutes
Toolbox Summary - The Central Limit Theorem10 minutes
Why the Practice Assignment is after the Graded Assignment10 minutes
Optional Reading - The Normal Distribution10 minutes

2 assignmentsTotal 60 minutes

Normal Distribution - Practice for Final Assignment30 minutes
Test Yourself: Normal Distribution 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 videosTotal 20 minutes

Statistical Inference5 minutes
Steps of Hypothesis Testing6 minutes
Z-test for a One Sample Hypothesis Test6 minutes
t-test for a One Sample Hypothesis Test4 minutes

8 readingsTotal 80 minutes

Download the Module 5 Workbooks10 minutes
At the end of this module - your final Excel file should look like this10 minutes
Toolbox Summary - Statistical Inference10 minutes
Toolbox Summary - Hypothesis Testing10 minutes
Hypothesis Testing for One Sample Tests10 minutes
Why the Practice Assignment is after the Graded Assignment10 minutes
Optional Reading - Statistical Inference10 minutes
Summary of the Course and Next Steps10 minutes

3 assignmentsTotal 90 minutes

Statistical Inference - Practice for Final Assignment30 minutes
Test Yourself: Statistical Inference30 minutes
Final Assignment - Excel Skills for Statistics and Data Analysis: Essentials30 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

What's included

8 readings

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructor

Assoc Prof Prashan S. M. Karunaratne

28 Courses1,699,365 learners

Offered by

Macquarie University

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Frequently asked questions

Yes. This course is designed for learners with no prior background in statistics or data analysis. It starts from foundational concepts — including what statistics is and why it matters — and builds progressively through to hypothesis testing. If you're comfortable using a computer and working with numbers, you have everything you need to get started.

Basic familiarity with Excel is helpful, but the course is designed to be accessible even if you're relatively new to it. Each module includes downloadable workbooks and step-by-step demonstrations so you can follow along and build your skills as you go. An optional fifth module also provides supplementary Excel toolbox content — covering charting, data cleaning, named ranges, and more — for learners who want to go further.

Descriptive statistics summarise and describe the features of a dataset — such as averages and spread. Inferential statistics allow you to draw conclusions about a wider population based on a smaller sample. This course covers both: the first two modules focus on descriptive statistics, while Modules 3 and 4 introduce the normal distribution and inferential methods including hypothesis testing.

Many statistics courses focus on programming languages like Python or R. This course uses Microsoft Excel — a tool most professionals already have access to — making statistical concepts immediately applicable in everyday work. The focus on practical, hands-on Excel workbooks means you're building usable skills from the very first module, not just learning theory.

Each week includes short video lectures, a downloadable Excel workbook to follow along with, toolbox summary readings as reference resources, a graded "Test Yourself" assignment, and a practice assignment you can use to build confidence before the next module. Dialogue activity helps you connect statistical concepts to real decision-making contexts.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.