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.