## Week 1

### Lesson 1- What Is Statistics, Anyway?

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

### Lesson 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'll learn to summarize data and describe its center along with its variability. As you learn to calculate mean, median, range, and standard deviation, I'll provide examples from different workplaces. You'll see how statistics plays a part in medicine, human resources, education, politics, finance, and marketing.

## Week 2

### Lesson 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'll 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. Our examples in this lesson come from medicine, mortgage lending, classrooms, biologists' field notes, and the aisles of your local grocery store.

### Lesson 4- Displaying Qualitative Data: Percentages, Charts, and Graphs

"How much satisfaction do you get from your friendships?" "Would you vote for a qualified woman for president?" "Which mountain in the Himalayas is most dangerous to climb?" In Lesson 4, you'll learn to summarize and display qualitative data from questions like these. We'll focus on charts and tables, and along the way you'll see examples from business, government, and medicine.

## Week 3

### Lesson 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? In Lesson 5, we'll look at relationships between two quantitative variables. You'll learn to make scatterplots and describe what you see. You'll also use correlation to measure the strength of a particular link.

### Lesson 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 CO_{2} levels in the atmosphere? In Lesson 6, we'll go beyond describing and measuring association between variables. You'll use *linear regression* to find an equation that models the data. Then you'll use the equation to make predictions.

## Week 4

### Lesson 7- What's the Chance of That? Probability Concepts

What's the chance you'll have a coin come up "heads" five times in a row? What about drawing four aces from a deck of cards or picking the winning lottery numbers? In Lesson 7, we'll study the basics of probability. You'll learn the rules that govern probability and see how to apply them in a variety of situations.

### Lesson 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? In Lesson 8, we'll talk about probability models and expected value. Our focus will be the most common probability model in statistics: the normal model. You'll see this bell-shaped distribution in a variety of settings, and you'll learn to use it to estimate probabilities.

## Week 5

### Lesson 9- The Key to Inference: Sampling Distributions

How can we move beyond the sample at hand to make predictions and draw conclusions about the population? In Lesson 9, you'll discover the key that lets you make inferences about the population. You'll see the most important result in all of statistics—the central limit theorem—and you'll learn why the normal model plays such an important role in statistics. You'll also find out how to use data and probability to evaluate a claim.

### Lesson 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? In Lesson 10, we'll begin our journey into statistical inference by focusing on confidence intervals for proportions. You'll learn to calculate the margin of error and use it to build an interval for estimating a population proportion. You'll also see how to estimate the sample size you'd need for a survey.

## Week 6

### Lesson 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'll learn to answer questions such as these by testing an appropriate hypothesis using proportions. You'll find out what steps make up a hypothesis test and how you can interpret the results, make inferences, and arrive at informed decisions.

### Lesson 12- Inference About Means

How do you test hypotheses about means? For example, how can you use a confidence interval to estimate the average number of hours Americans use the Internet each week? In our last lesson together, you'll get an introduction to inference for means. You'll learn to calculate and interpret confidence intervals and hypothesis tests for a mean, and you'll see how to analyze data from a paired experiment. And while we're at it, you'll find out what the history of statistics has to do with the quality of beer in Ireland.