Texts: Random Variables
What is a discrete random variable? And what does its probability distribution look like or consist of? Can you look at a probability distribution and estimate its center and spread? What does a standard deviation look like if the distribution is roughly mound-shaped and symmetric? On Page 100, in the comment, you can read, "The distribution in which it is more likely to find values that are further from the mean will have a larger standard deviation. Likewise, the distribution in which it is less likely to find values that are further from the mean will have a smaller standard deviation." What does this mean to you and how can you capture that idea with pictures and labels on your summary sheet? What is a continuous random variable? And how are probabilities of such random variables related to areas? If you've studied calculus, you might ask how you could use calculus to find probabilities. What is the transition from discrete to continuous random variables? Review the comments and summary on Page 104. What part do you still have questions about? What must the area under a continuous probability distribution equal?
Looking Ahead (Optional for Now)
Summarize what you know about normal distributions, find some good images, and figure out how you will find related probabilities... TI-84, Excel, or Beoga App? (Or if you know how to program in R, maybe you'll get them that way.) For sure, include the Standard Deviation Rule for Normal Random Variables on your summary sheet! I think this is a great image to include from Page 106: