The second midterm is on Wednesday, April 9, during the regular class period.
The following is a chapter by chapter guide intended to help you organize the material we have covered in class as you study for your exam. It is only intended to serve as a guideline, and may not explicitly mention everything that you need to study. It is also important you are comfortable with material from previous pre-requisite classes.
Please review all homework and quiz problems for the chapters given below, as well as examples worked out in class and in the textbook. This includes material covered in Exam 1. You are also encouraged to work out the "self-test problems and exercises" at the end of each section for more practice. In addition, Prof. Eugene Speer has an excellent collection of review problems on his website.
5.1: This section deals with continuous random variables. You should know how to compute the probability that such a variable lies within a certain range using the probability density function or the cumulative distribution function. You should also know how to get the cumulative distribution function from the probability density function and vice versa.
5.2: Make sure you can compute the expectation and variance for a continuous random variable and understand how these change for functions of the random variable.
5.3: You should be able to identify situations described by a uniform random variable, and know how to determine the probability density for a variable that is uniformly distributed over a given range.
5.4 & 5.4.1: You should know when it is appropriate to use a normal distribution to describe a random variable. You will be given the probability density function for the normal distribution and a copy of Table 5.1, which gives values of the cumulative distribution of the standard normal distribution. You should be able to use this table to determine probabilities for any normally distributed variable. You should also know how to use normal distributions to approximate a binomial distribution, including how to determine the appropriate mean and variance for this distribution, and applying a continuity correction where appropriate.
5.5 & 5.5.1: You will be given the density function for an exponential distribution, and you should be able to recognize where it is appropriate to use it, including situations in which it relates to the Poisson distribution. You should know how what it means for a distribution to be memoryless. You should also know what the hazard rate for a random variable is, and be able identify a distribution with a constant hazard rate as an exponential.
6.1: This section deals with joint probabilities for two or more random variables. You should be able to determine probabilities and marginal distributions from the joint distribution functions or joint mass functions or joint density functions, as appropriate.
Maintained by ynaqvi and last modified 03/30/14