Introduction to Statistics

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

Is there an easier way of understanding data than peering at column after column of numbers? Yes. In this lesson, 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.

"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.

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.

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

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

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.

How do you move beyond the sample at hand to make predictions and draw conclusions about the population? In this lesson, 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.

"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.

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

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. You will also find out what the history of statistics has to do with the quality of beer in Ireland.