Tentative schedule

Week Text section Suggested problems

1 1 Introduction to Statistics and Data Analysis

1.2--8 The role of probability, Measures of location and

variability, Discrete and continuous data p.20: 1 – 5

2 2 Probability

2.1--2 Sample spaces and events; Venn diagram p.29: 2, 3, 8, 10, 12, 14, 18

2.3 Counting techniques p.38: 2, 4, 6, 10, 14, 18, 26

2.4 – 5 Probability; the additive rule and mutually exclusive

events; complementary events p.46: 2, 4, 6, 8, 10, 14

3 2.6 Conditional probability p.54: 1, 2, 4, 8, 10, 14

2.7 The multiplicative rule and independent events p.54: 16, 18, 19, 20,

2.8 Bayes’ rule p.60: 2, 4, 6, 7, 8; p.49: 1

4 3 Random Variables and Probability Distributions

3.1-- 3 Two types of random variables p.72: 2 – 6, 8, 10 –14, 21, 24, 26

1.8 Stem and leaf displays, histograms p.20: 2, 4

3.4 Joint probability distributions p.84: 2, 4, 6, 8, 10, 12, 14, 18, 20, 24

4. Mathematical Expectation

5 4.1 Expected values of discrete random variables p.94: 2, 4, 6, 8—14, 24, 25

4.2 Variance and covariance p.102: 2—8, 12, 14

4.3 Linear combination of random variables p.112: 2—6, 20, 22

5. Some Discrete Probability Distributions

6 5.1--3 Uniform and binomial random variable; p.124: 1—8, 10—13, 16, 20,

5.4--5 Hypergeometric and negative binomial p.131: 1—6, 10, 20

7 3.6 The Poisson probability distribution p.139: 4, 6,8, 10, 12, 14, 20

6. Continuous Probability Distributions

6.1--4 Uniform and normal distribution; use of tables p.156: 2—6, 8, 10, 14

8 6.5 Normal approximation to the binomial p.164: 1, 2, 4, 6, 12

6.6–10 The exponential distribution p.174: 1, 2, 6

7 Functions of Random Variables

9 7.3 Moments and moment generating functions p.191: 16--21

8 Random Sampling, Data Description, and Some

Fundamental Sampling Distributions

8.1–2 Some important statistics p.200: 2—8, 15

10 8.3 Graphical methods p.:

8.4–5 Sampling distribution of mean p.215: 2—6, 10, 12, 14

8.6–8 Sampling distribution of S² p.227: 1—6, 10, 12, 16

11 9 One- and Two-Sample Estimation Problems

9.1–7 Confidence Intervals Based on a Single Sample p.245: 4—8, 14, 16

9.8–9 Two-Sample Estimation Problems p.255: 1—4, 10, 12

12 9.10–9.11 Estimating a proportion p.262: 1—6, 10, 16, 20

9.12–13 Estimating the variances p.268: 2—4, 8

9.15 Maximum likelihood estimation p.280: 1—5

* This schedule is subject to change for the optimum benefit of the class as a whole. Therefore it is important to stay alert and attend class regularly.