Making sense of the course from the data: Statistics Explained. Who was the greatest baseball player of all time? How likely is an opinion poll to be correct? Is it wise to buy last year’s highest-performing stock? Which hospital has the best results for a particular procedure? When is it a good idea to buy an extended warranty on a product? All of these questions involve the interpretation of statistics, along with a surprising number of other mysteries, including: Is the “hot hand” among sports players real? How can you tell if Shakespeare is the likely author of a newly discovered poem? What is a guilt-free way to confess infidelity to someone? And how Does the tax assessor calculate the market value of a home?
Making Sense of Data: Statistics Made Clear is an introduction to a very important topic in today’s data-driven society. In 24 half-hour lectures, you’ll explore the theories and methods that underlie the study of statistics. You have probably heard terms such as mean, median, percentiles, quartiles, statistical significance. And Bell curve and you’ll have an idea of what they mean. This course will sharpen your understanding of these and many other statistical concepts and show how they can be used correctly to extract meaning from data.
Become Statistically Savvy: These challenging but accessible lectures assume no background in mathematics beyond basic algebra. While most introductory college statistics courses emphasize solving technical problems and plugging data into formulas, this course focuses on the logical foundations and fundamental strategies of statistical reasoning, illustrated with numerous examples. Professor Michael Starbird guides you through the most important equations, but his emphasis is on the role of statistics in everyday life, giving you an overview of how statistical tools can be used in risk assessment, university admissions, drug testing, fraud investigations, and hosting, among other applications
Statistical Adventures: Professor Starbird is a master at conveying concepts through examples. Here are some of these:
- When is the lottery not drawn? When it’s not really random. In the 1969 Vietnam War draft lottery, young men of draft age were given an induction rating based on their birthday, placed in capsules and drawn from a container, apparently at random. But by calculating the statistical correlation for the draw order, it becomes clear that a non-random variable is at play. The most likely explanation is that the capsules were not mixed well enough with the dates.
- Birthday Challenge: What is the probability that two of 50 random people have the same birthday? The odds are greater than most people think.
- Chicken Soup Recipe: How can 1,000 randomly selected people predict the behavior of tens of millions of voters? This is the nature of a political survey, and its effectiveness should be no more surprising than the fact that the taste of chicken soup is sufficient to predict the overall saltiness of a batch, whether that batch is in a single cup or a giant pot.
- Beware of fallacious reasoning: In the O.J. Simpson murder trial, Simpson’s attorney Johnnie Cochran refuted evidence that Simpson had beaten his wife with the statistic that only 1 in 1,000 women murder their spouse. Therefore, Cochran argued, there was only a 1 in 1,000 chance that Simpson would commit the murder. Professor Starbird discusses the fallacies of this argument, including that the wife in this case was actually murdered, so the relevant question should be: What is the probability that she was beaten beforehand?
- Who really won the presidential election of 1860? Establishing the will of the people in an election can be difficult, especially when three or more candidates are involved. Professor Starbird shows how the results of the four-way presidential race of 1860 could be interpreted as a victory for each of the three candidates, depending on the voting scheme used. Abraham Lincoln won under the current rules, but under other, equally valid rules, the winner – and history – would have been very different.
Statistics are everywhere: Statistical information is literally everywhere. You can’t look at a newspaper without seeing statistics on almost every page. You can’t talk about weather forecasts without citing statistics. Statistics arise most obviously in business and the social sciences, but even enter the arts in the analysis of manuscripts. And it’s better not to go to the casino without understanding statistics. “It’s actually harder to find places where statistics don’t matter than it is to find places where they do matter says Professor Starbird.