Introduction to Statistics (Self-Paced Tutorial)


Improve your understanding of data and learn how to develop graphs and charts.


Do you need an introduction to statistics or maybe just a refresher? Do you want to improve your understanding of data and use it to make decisions? If you’re looking for help with statistics, this online statistics course is for you!

With easy-to-understand examples combined with real-world applications, this course provides you with the skills and knowledge you need to start analyzing data. You will learn how to use, collect, and then apply data to real-life problems with charts, numbers, and graphs.

Beyond that, you will learn ways to visualize and measure relationships to make forecasts and predictions. Throughout the course, you will use real data and a variety of examples drawn from business and industry, health care, sports, education, politics, and the social sciences.


Hardware Requirements:

  • This course can be taken on either a PC or Mac device.

Software Requirements:

  • PC: Windows 8 or newer.
  • Mac: OS X Snow Leopard 10.6 or later.
  • Browser: The latest version of Google Chrome or Mozilla Firefox are preferred. Microsoft Edge and Safari are also compatible.
  • Adobe Acrobat Reader.
  • Software must be installed and fully operational before the course begins.


  • Email capabilities and access to a personal email account.

Course Outline

1 What Is Statistics, Anyway?

What do you know about statistics? How do you collect reliable data and use it to make informed decisions? In Lesson 1, you will learn some of the concepts and terms needed throughout the course. You will also find out how statistics affect events in the news and in your everyday life.

2 Quantitative Data: From Averages to z-Scores

Once you have a set of data, how can you summarize and interpret it to figure out what it really means? In Lesson 2, you will learn to summarize data and describe its center along with its variability. You will see how statistics plays a part in medicine, human resources, education, politics, finance, and marketing.

3 Displaying Quantitative Data: Dots, Plots, and Histograms

Is there an easier way of understanding data than peering at column after column of numbers? Yes. In Lesson 3, you will see quantitative data displayed in dot plots, histograms, and many other forms. Knowing how to read and construct these graphs will help you see patterns and spot unusual values in data.

4 Displaying Qualitative Data: Percentages, Charts, and Graphs

"How much satisfaction do you get from your friendships?" "Which mountain is most dangerous to climb?" This lesson focuses on summarizing and displaying qualitative data from questions like these. You will use charts and tables to analyze real-world examples in business, medicine, and more.

5 Is There a Link? Scatterplots and Correlation

Is there a link between the poverty rate and the crime rate? Is your score on a math exam related to your anxiety level? This lesson looks at relationships between two quantitative variables. You will learn to make scatterplots and describe what you see.

6 Linear Regression: How Can We Predict the Future?

Can we predict the next world-record time in the mile run? How can we forecast CO2 levels in the atmosphere? This lesson dives into describing and measuring the association between variables. You will use linear regression to find an equation that models the data and use the equation to make predictions.

7 What's the Chance of That? Probability Concepts

What's the chance you will have a coin come up "heads" five times in a row? Lesson 7 explores the basics of probability. You will learn the rules that govern probability and see how to apply them in a variety of situations.

8 Probability Models: What's Normal?

What should you expect to happen in a game involving chance? How can you estimate the probability that a healthy baby will be born underweight? This lesson focuses on probability models and expected value. You will learn about the most common probability model in statistics: the normal model.

9 The Key to Inference: Sampling Distributions

How do you move beyond the sample at hand to make predictions and draw conclusions about the population? In Lesson 9, you will discover the key that lets you make inferences about the population. You will see the most important result in all of statistics—the central limit theorem.

10 How Certain Are We? Confidence Intervals for Proportions

"The margin of error for this poll is plus or minus 3%." What does that mean, anyway? This lesson introduces statistical inference and focuses on confidence intervals for proportions. You will learn to calculate the margin of error and use it to build an interval for estimating a population proportion.

11 Trial by Data: Testing Hypotheses About Proportions

Is there really a home team advantage in sports? Did that television ad your company bought result in increased awareness of your product? In Lesson 11, you will learn to answer questions such as these by testing an appropriate hypothesis using proportions.

12 Inference About Means

How do you test hypotheses about means? For example, can you use a confidence interval to estimate the average number of hours Americans use the Internet each week? Your last lesson introduces inference for means. You will learn to calculate and interpret confidence intervals and hypothesis tests for a mean. And you will find out what the history of statistics has to do with the quality of beer in Ireland.