Open course ware

The graph shows on the horizontal axis the percentage of questions answered, and on the vertical axis, the percentage of answers that were correct. When Watson started, the graph that shows its performance is shown here. In 2007, we observed that the performance of Watson improved, and it is shown there. And then successively from 2008 May to 2010, we see the successive improvement of Watson in this graph that shows a trade-off between questions answered and precision. This is the area of the best human players. Observe that they answer a high number of questions and they answer a very high number of questions correctly. So it was at that time-- 2010-- that the people that controlled the decision decided that Watson is ready to enter the competition. So the games were scheduled for February 2011. Two games were played, and the winner would be the contestant with the highest winnings over the two games. Once we got into the game, it was nerve-wracking, frankly. Brad, if yo...

This plot shows two of our independent variables, the number of office visits on the x-axis and the number of narcotics prescribed on the y-axis. Each point is an observation or a patient in our data set. The red points are patients who received poor care, and the green points are patients who received good care. It's hard to see a trend in the data by just visually inspecting it. But it looks like maybe more office visits and more narcotics, or data points to the right of this line, are more likely to have poor care. Let's see if we can build a logistic regression model in R to better predict poor care. In our R console, let's start by reading our data set into R. Remember to navigate to the directory on your computer containing the file quality.csv. We'll call our data set "quality" and use the read.csv function to read in the data file quality.csv. Let's take a look at the structure of our data set by using the str function. We have 131 ob...