Probability and Statistics

Probability and Statistics

MTH 23
Section 2478

Tuesday,Thursday, 10:00am-11:15am, room CP B2

Syllabus

Prerequisite for this course is MTH04 or equivalent.

Chapter

Section

Topic

Suggested Problems

1. Getting started
1.1
What is statistics? p. 10-11 / 1-9

1.2
Random Samples p. 17-18 / 1-10

2. Organizing Data
2.2
Bar Graphs, Circle Graphs, and Time-Series Graphs p. 54-56 / 1-10

2.3
Stem-and-Leaf Displays p. 61-64 / 1-10

2.1
Frequency Distributions, Histograms, and Related Topics p. 43-46 / 1-12

3. Averages and Variation
3.1
Measures of Central Tendency: Mode, Median, Mean p. 80-82 / 1-12

3.2
Measures of Variation p. 93-97 / 1-9

3.3
Percentiles and Box-and-Whisker Plots p. 106-108 / 1-10

4. Regression and Correlation
4.1
Scatter Diagrams and Linear Correlation p. 131-136 / 1-12

4.2
Linear Regression and the Coefficient of Determination p. 146-151 / 1-10

5. Elementary Probability Theory
5.1
What is Probability? p. 167-169 / 1-11

5.2
Some Probability Rules - Compound Events p. 182-187 / 1-15

6. The Binomial Probability Disctribution
6.1
Introduction to Random Variables and Probability Distributions p. 213-216 / 1-10

6.2
Binomial Probabilities p. 225-229 / 1-12

6.3
Additional Properties of the Binomial Distribution p. 234-236 / 1-9

7. Normal Curves and Sampling Distributions
7.1
Graphs of Normal Probability Distributions p. 253-255 / 1-11

7.2
Standard Units and Areas Under the Standard Normal Distribution p. 266-268 / 1-48

7.3
Areas Under Any Normal Curve p. 277-280 / 1-26

7.6
Normal Approximation to the Binomial Distribution p. 301-304 / 1-8

7.4
Sampling Distributions (optional) p. 285 / 1-9

7.5
The Central Limit Theorem (optional) p. 293-296 / 1-8

8. Estimation
8.1
Estimating \mu When \sigma is Known p. 324-327 / 1-10

8.2
Estimating \mu When \sigma is Unknown p. 335-339 / 1-10

8.3
Estimating p in the Binomial Distribution p. 347-350 / 1-8

9. Hypithesis Testing
9.1
Introduction to Statistical Tests p. 372-375 / 1-8

9.2 Part I
Testing the Mean \mu When \sigma is Known p. 388-389 / 1-8

9.2 Part II
Testing \mu When \sigma in Unknown (optional) p. 389-391/ 9-16

9.2 Part III
Tesing \mu Unsing Critical Regions (Traditional Method) (optional) p.393 / 21-26

9.3
Testing a Proportion p (optional) p. 400-403 / 1-9

Chapter	Section	Topic	Suggested Problems
1. Getting started	1.1	What is statistics?	p. 10-11 / 1-9
	1.2	Random Samples	p. 17-18 / 1-10

2. Organizing Data	2.2	Bar Graphs, Circle Graphs, and Time-Series Graphs	p. 54-56 / 1-10
	2.3	Stem-and-Leaf Displays	p. 61-64 / 1-10
	2.1	Frequency Distributions, Histograms, and Related Topics	p. 43-46 / 1-12

3. Averages and Variation	3.1	Measures of Central Tendency: Mode, Median, Mean	p. 80-82 / 1-12
	3.2	Measures of Variation	p. 93-97 / 1-9
	3.3	Percentiles and Box-and-Whisker Plots	p. 106-108 / 1-10

4. Regression and Correlation	4.1	Scatter Diagrams and Linear Correlation	p. 131-136 / 1-12
	4.2	Linear Regression and the Coefficient of Determination	p. 146-151 / 1-10

5. Elementary Probability Theory	5.1	What is Probability?	p. 167-169 / 1-11
	5.2	Some Probability Rules - Compound Events	p. 182-187 / 1-15

6. The Binomial Probability Disctribution	6.1	Introduction to Random Variables and Probability Distributions	p. 213-216 / 1-10
	6.2	Binomial Probabilities	p. 225-229 / 1-12
	6.3	Additional Properties of the Binomial Distribution	p. 234-236 / 1-9

7. Normal Curves and Sampling Distributions	7.1	Graphs of Normal Probability Distributions	p. 253-255 / 1-11
	7.2	Standard Units and Areas Under the Standard Normal Distribution	p. 266-268 / 1-48
	7.3	Areas Under Any Normal Curve	p. 277-280 / 1-26
	7.6	Normal Approximation to the Binomial Distribution	p. 301-304 / 1-8
	7.4	Sampling Distributions (optional)	p. 285 / 1-9
	7.5	The Central Limit Theorem (optional)	p. 293-296 / 1-8

8. Estimation	8.1	Estimating \mu When \sigma is Known	p. 324-327 / 1-10
	8.2	Estimating \mu When \sigma is Unknown	p. 335-339 / 1-10
	8.3	Estimating p in the Binomial Distribution	p. 347-350 / 1-8

9. Hypithesis Testing	9.1	Introduction to Statistical Tests	p. 372-375 / 1-8
	9.2 Part I	Testing the Mean \mu When \sigma is Known	p. 388-389 / 1-8
	9.2 Part II	Testing \mu When \sigma in Unknown (optional)	p. 389-391/ 9-16
	9.2 Part III	Tesing \mu Unsing Critical Regions (Traditional Method) (optional)	p.393 / 21-26
	9.3	Testing a Proportion p (optional)	p. 400-403 / 1-9