Review Exam 2, Math 201 (B. Olson)

(NO continuity correction for sections 6.4 and 7.3)

Chapter 5:  The Binomial Distribution

1.  What is the difference between a discrete random variable and a continuous random variable?

2.  What is a probability distribution?

3.  What is the expected value of a random variable x in a probability distribution?

4.  What is a binomial experiment?  (Page 221)

5.  How do you compute the probabilities for a binomial experiment?

Chapter 6:  The Normal Distribution

1.  What are the properties of a normal curve?  (Page 273)

2.  The normal curve uses what parameters? 

3.  What is the empirical rule for normal curve?  (Page 276)

4.  How do you construct a Control Chart? What are the Out-of-Control Signals?  (Pages 280-281)

5.  What are the values of  and  in a Standard Normal Distribution?

6.  What is the purpose of a Standard Normal Distribution?

7.  How do we convert raw scores (x) into Standard units (z-scores) and vice-versa?

8.  How do we find the area under a standard normal curve given a z value?  (Page 297)

9.  How do we find a z-value given the probability (or area under the curve)?

10.  What must be necessary to use a Normal approximation to the Binomial Distribution?

11.  What are the conversions for the variables needed from the binomial distribution to the standard normal?

Chapter 7:  Sampling Distributions

1.  What is the difference between a distribution of a sample and a sampling distribution?

2.  What is a parameter and give examples?

3.  What is a statistic and give examples?

4.  What is Theorem 7.1?  (Page 341)

5.  What is the Central Limit Theorem?  (Page 344)

6.  What makes the Central Limit Theorem different from Theorem 7.1?

7.  What are the conversions for the variables needed in both theorems to convert to a standard normal? (Pages 342 & 345)

8.  What is the sampling distribution for the proportion p = ?  (Page 353)

9.  What is a P-Chart?  (Pages 358-359)

Chapter 8:  Estimation

1.  What is a point estimate?       What is a critical value?

2.  What is the formula for finding the maximal error tolerance, E in large samples?  (Page 378)

3.  What is a confidence interval?

4.  Why are we not allowed to use a z variable when estimating the mean with small samples?

5.  What distribution is used for estimating the mean for small samples?  What is the formula for the maximal error tolerance?

6.  What formula is used for estimating p in large samples in a Binomial Distribution?

7.  When choosing a sample size for estimating the mean, what are the criteria?

8.  What is the formula to find sample size?  What about the sample size for estimating p?

9.  When estimating the difference of means between two populations, what does Theorem 8.1 tell us?  (Page 422)

10.  When finding a c confidence interval for what do we need?

For large samples  (Page 423)              For Small samples  (Page 426)

11.  When finding a c confidence interval for p₁ – p₂ (large samples) what do we need? (Pg. 429)

12.  What does it mean when the difference of two population means is between two positive values?  What if one value is negative and the other is positive?

Read Chapter Summaries for Sections 5.1 & 5.2 (Pages 260 – 261), Chapter 6 (Pages 324 – 325), Chapter 7 (Pages 364 - 365) and Chapter 8 (Pages 439 – 440).

Go over homework and class notes.

Larry Green has a practice midterm 2 for his class at this website.  Note his second midterm covers different sections.  http://www.ltcconline.net/greenl/courses/201/keys/pMid2.htm