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Math 3680.002: Fall 2016

Meets: TR 5:00-6:20 in Business Leadership Building, Room 250.

Instructor: Professor John Quintanilla

Office: GAB, Room 418-D

Office Phone: x4043

E-mail: There are three ways to reach me by e-mail.

1.      My usual e-mail address: jquintanilla@unt.edu.

2.      Through Enhanced Webassign: click Communication near the top of the Enhanced WebAssign page and then follow the prompts.

3.      Through Enhanced WebAssign: when doing your homework, click Ask Your Teacher near the top of the Enhanced WebAssign page and then follow the prompts. If you have a question about a specific homework problem, this is perhaps the best way to communicate with me, as I can see both your message and your previous attempts at doing your homework.

Web page: http://www.math.unt.edu/~johnq/Courses/2016fall/3680/

Office Hours: Mondays and Wednesdays 11-2, or by appointment. I'm fairly easy to find, and you're welcome to drop by outside of office hours without an appointment. However, there will be occasions when I'll be busy, and I may ask you to wait or come back later.

Required Text: Probability & Statistics for Engineering and the Sciences, 9th edition, by J. L. Devore. There are two options for purchasing this text. The second option is cheaper; however, this only provides temporary online access to the textbook, so that you would neither be able to use a physical hard copy of the book this semester nor permanently add it to your bookshelf after completing the course. Both can be purchased at http://www.cengagebrain.com/course/site.html?id=1-1MH23VQ.

·         ePack: Probability and Statistics for Engineering and the Sciences, 9th + Enhanced WebAssign Instant Access for Statistics, Single-Term Courses. ISBN 978-1-305-77938-9.

·         Enhanced WebAssign Instant Access for Statistics, Single-Term Courses, 1st Edition. ISBN 978-1-285-85804-3.

Strongly Recommended: Lecture notes for the semester can be purchased from the Eagle Images Print Center for approximately $25. The Eagle Images Print Center is in room 221 of the University Union.

The lecture notes for the semester will also be available on Blackboard. You are welcome to print these out at home; however, be aware that it's probably far cheaper to purchase the notes at Eagle Images than to purchase the ink cartridges and paper necessary to print out all of the notes. If you have sufficient print credits, you also can print these on campus. For more information about print credits and other rules and regulations regarding the use of printers on campus, please see http://computerlabs.unt.edu/printing.

Technology: You will be expected to bring to class --- including exams --- either a laptop computer with a spreadsheet program (such as Microsoft Excel or Open Office Calc) or else a calculator that can perform multiple statistical functions. In class, I will demonstrate how to use Microsoft Excel and a TI-83 Plus to perform various statistical functions. If you have some other kind of calculator, you are welcome to ask me before or after class about how to use its statistical functions.

Course Description: Descriptive statistics, elements of probability, random variables, confidence intervals, hypothesis testing, regression, contingency tables.

Prerequisite: Math 1710 and Math 1720 (may be taken concurrently).


What You Should Do Immediately

To get started with Enhanced WebAssign, visit http://www.webassign.net/manual/WA_Student_Quick_Start.pdf. In particular, you will need to visit www.webassign.net and use the following Class Key Code: unt 6797 8025

I strongly encourage you to get started with Enhanced WebAssign as soon as possible. If you delay, you run the risk of unforeseen technical problems that could prevent you from completing the first assignments (both due on Friday, September 9, with a bonus possible if submitted by September 7).

While Enhanced WebAssign is required for the course, it is my understanding that, at the start of the semester, you have a 14-day grace period to use Enhanced WebAssign for free. After this grace period, a code must be entered to continue to use Enhanced WebAssign.


Course Topics

The following chapters and sections of the textbook will be covered according to the projected schedule below. Dates may change as events warrant.

  • Chapter 1: Overview and Description Statistics
    • 1.1 Populations, Samples and Processes
    • 1.2 Pictorial and Tabular Methods in Descriptive Statistics
    • 1.3 Measures of Location
    • 1.4 Measures of Variability
  • Chapter 2: Probability
    • 2.1 Sample Spaces and Events
    • 2.2 Axioms, Interpretations, and Properties of Probability
    • 2.4 Conditional Probability
    • 2.5 Independence
  • Chapter 3: Discrete Random Variables and Probability Distributions
    • 3.1 Random Variables
    • 3.2 Probability Distributions for Random Variables
    • 3.3 Expected Values
    • 3.4 The Binomial Probability Distribution
    • 3.5 Hypergeometric and Negative Binomial Distributions
  • Chapter 4: Continuous Random Variables of Probability Distributions
    • 4.1 Probability Density Functions
    • 4.2 Cumulative Distribution Functions and Expected Values
    • 4.3 The Normal Distribution
    • 4.6 Probability Plots
  • Chapter 5: Joint Probability Distributions and Random Samples
    • 5.4 The Distribution of the Sample Mean
    • 5.5 The Distribution of a Linear Combination
  • Chapter 7: Statistical Intervals Based on a Single Sample
    • 7.1 Basic Properties of Confidence Intervals
    • 7.2 Large-Sample Confidence Intervals for a Population Mean and Proportion
    • 7.3 Intervals Based on a Normal Population Distribution
  • Chapter 8: Test of Hypotheses Based on a Single Sample
    • 8.1 Hypotheses and Test Procedures
    • 8.2 Tests About a Population Mean
    • 8.3 Tests Concerning a Population Proportion
    • 8.4 P-Values
  • Chapter 9: Inferences Based on Two Samples
    • 9.1 z Tests and Confidence Intervals for a Difference Between Two Population Means
    • 9.2 The Two Sample t Test and Confidence Interval
    • 9.3 Analysis of Paired Data
    • 9.4 Inferences Concerning a Difference Between Population Proportions
  • Chapter 12: Simple Linear Regression
    • 12.2 Estimating Model Parameters
    • 12.5 Correlation
  • Chapter 13: Nonlinear and Multiple Regression
    • 13.2 Regression with Transformed Variables
  • Chapter 14: Goodness-of-Fit Tests and Categorical Data Analysis
    • 14.1 Goodness-of-Fit Tests When Category Probabilities Are Completely Specified
    • 14.3 Two-Way Contingency Tables

 

August 30

Lecture #1

1.2, 1.3

Graphical Representation of Data

Page 3: Box and Whisker Plots

 

September 1

Lecture #1

1.3, 1.4

Graphical Representation of Data

Page 7: Histograms

September 6

Lecture #2

1.3, 1.4

Mean and Standard Deviation

Pages 2-3: Trimmed Means

Page 5: Mean and SD

September 8

Lecture #3

2.2, 2.4

Probability: Axioms and Multiplication Rule

Page 2: Probability

Page 5: Multiplication Rule

Page 7: Tree Diagram

September 13

Lecture #4

2.2, 2.5

Probability: Independence and Addition Rule

Page 2: Independence

Page 3A: Multiplication Rule

Page 3B: Parallel/Series

Page 8A: Deck of Cards

Page 8B: Venn Diagram

Page 9: Venn Diagram

September 15

Lecture #5

3.1, 3.2, 3.3

Discrete Random Variables and Probability Distributions

Page 2: Cumulative Distribution Function

Page 5: Mean and SD

September 20

Lecture #6

3.4, 3.5

Binomial and Hypergeometric Distributions

Pages 5-6: Binomial

Page 9: Hypergeometric

September 22

Lecture #7

4.1, 4.2

Continuous Random Variables

Page 2: Probability and Cumulative Distribution Function

Page 3: Percentile

Page 5: Mean and SD

September 27

Lecture #8

4.3

The Normal Distribution

Page 4: Probability

Page 5: Percentile

September 29

Exam #1

Chapters 1-3

 

Lectures 1-6

Review #1

The videos below give the solutions to each of the review exercises. I encourage you to attempt each problem on your own before watching the videos.

 

1.1   1.2   1.3   1.4   1.5   1.6,7,8

1.9,10,11   1.12,13   1.14   1.15

October 4

Lecture #9

4.3, 5.4

Approximating Bin(n,p) with the Normal Distribution

Page 4: Normal Approximation of Binomial Distribution

October 6

Lecture #10

4.6, 5.5

Probability Plots and Linear Combinations of Random Variables

Page 2: Probability Plot

October 11

Lecture #11

5.4

The Central Limit Theorem

Page 6: Estimating Probability Involving a Sum

October 13

Lecture #12

7.1, 7.2

Confidence Intervals: Large samples or known s

Page 7: Two-Sided Confidence Interval for a Population Mean

October 18

Lecture #13

7.2

Confidence Intervals: One-Sided for Means and Two-Sided for Proportions

Page 3: One-Sided Confidence Interval for a Population Mean

Page 6: Two-Sided Confidence Interval for a Proportion

October 20

Lecture #14

7.3

Confidence Intervals and Prediction Intervals: Small Samples

Page 3: t Distribution

Page 5: Two-Sided Confidence Interval for a Population Mean (Small Sample)

Page 7: Prediction Interval

October 25

Lecture #15

8.1

Introduction to Hypothesis Testing

To be added later

October 27

Exam #2

Chapters 4-7

 

Lectures 7-14

Review #2

The videos below give the solutions to each of the review exercises. I encourage you to attempt each problem on your own before watching the videos.

 

2.1   2.2   2.3   2.4   2.5

2.6   2.7   2.8   2.9   2.10

2.11   2.12   2.13   2.14-15

2.16   2.17

 

Note: In 2.11, I discuss how to find critical values for the t distribution using a table.

November 1

Lecture #16

8.2

Hypothesis Testing: The z-Test

Page 1: Right-tailed z-Test

Page 7: Type II Error

Page 9: Sample size for a given value of b

November 3

Lecture #17

8.2

Hypothesis Testing: The z-Test and t-Test

Page 1: Left-tailed z-Test

Page 2: Type II Error and Sample Size

Page 4: Two-tailed z-Test

Page 6: Right-tailed t-Test

Page 9: Two-tailed t-Test

November 8

Lecture #18

8.3

Hypothesis Testing: The z-Test and Proportions

Pages 4-5: Right-tailed z-Test for a Proportion, Type II Error, and Sample Size

November 10

Lecture #18

8.3

Hypothesis Testing: The z-Test and Proportions

Pages 4-5: Right-tailed z-Test for a Proportion, Type II Error, and Sample Size

November 15

Lecture #20

9.1

Two-Sample Data: Unpaired Large Samples

Pages 1 and 5: Hypothesis test for the difference in the averages of two large samples

Page 6: Confidence intervals for the difference in the averages of two large samples

November 17

Lecture #21

9.2, 9.3, 9.4

Two-Sample Data: Unpaired Small Samples and Proportions

 

Note: The slides for Section 9.3 can be found here; they were inadvertently omitted from the lecture notes.

Page 1: Hypothesis test for the difference in the averages of two small samples

Page 7: Hypothesis test for the difference of two proportions

November 22

Lecture #22

12.5

Correlation

To be added later

November 24

NO CLASS; HAPPY THANKSGIVING

November 29

Lecture #23

12.2, 13.2

Linear and Intrinsically Linear Regression

Page 8: Intrinsically Linear Regression: Percolation

 

Page 9: Intrinsically Linear Regression: Planets

December 1

Exam #3

Chapters 8-9

 

Lectures 15-21A

Review #3

 

The videos below give the solutions to each of the review exercises. I encourage you to attempt each problem on your own before watching the videos.

 

3.1   3.2   3.3   3.4   3.5

3.6   3.7   3.8   3.9   3.10

3.11   3.12   3.13   3.14

3.15   3.16   3.17

December 6

Lecture #24

14.1, 14.3

The Chi-Squared Distribution

Page 8: Specified Proportions

Page 9: Testing Independence

December 8

Review

Chapters 12-14

 

Lectures 22-24

Review #4

 

The videos below give the solutions to each of the review exercises. I encourage you to attempt each problem on your own before watching the videos.

 

4.1   4.2   4.3   4.4

4.5   4.6   4.7

December 13,

5-6:20 pm

Final


Student Responsibilities


Grading Policies

You may find the advice of former Math 3680 students helpful.

The following schedule is tentative and is subject to capricious changes in case of extracurricular events deemed sufficiently important to the upper administration.

Final Exam

Tuesday, December 13, 5-6:20 pm

24%

Exam 1

c. Week 5

20%

Exam 2

c. Week 9

20%

Exam 3

c. Week 14

20%

Homework

16%

A

90% and above

B

80% and below 90%

C

70% and below 80%

D

60% and below 70%

F

below 60%

Cooperation is encouraged in doing the homework assignments. However, cheating will not be tolerated on the exams. If you are caught cheating, you will be subject to any penalty the instructor deems appropriate, up to and including an automatic F for the course. Refer to the following university site for the official policy with regards to academic dishonesty: http://vpaa.unt.edu/academic-integrity.htm.

Attendance is not required for this class. However, you will be responsible for everything that I cover in class, even if you are absent. It is my experience that students who skip class frequently make poorer grades than students who attend class regularly. You should consider this if you don't think you'll be able to wake up in time for class consistently.

The grade of "I" is designed for students who are unable to complete work in a course but who are currently passing the course. The guidelines are clearly spelled out in the Student Handbook. Before you ask, you should read these requirements.


Exam Policies


Homework Policies

o    Each part of each exercise can be attempted up to 10 times. In other words, you could submit answers to part (a) of Exercise #1 up to 10 times, and then you could move on to attempt part (b).

o    Your last submission will count as your final answer.

o    You can save your work without using a submission.

o    Some exercises will use randomization. In other words, it’s possible that every student will have slightly different questions with accordingly different answers.

o   Homework will be due every Friday at 11:59 pm.

o   A 5% bonus will be awarded to students who complete their homework more than 48 hours before the due date.

o   If requested no more than a week after the original due date (i.e., by the following Friday at 11:59 pm), it is possible to receive an automatic extension on homework through Enhanced WebAssign. Any work done after the automatic extension can be submitted for half credit as long as it completed within 24 hours of the request.


Note to TNT Students

 


Final Note

The University of North Texas makes reasonable academic accommodation for students with disabilities. Students seeking accommodation must first register with the Office of Disability Accommodation (ODA) to verify their eligibility. If a disability is verified, the ODA will provide you with an accommodation letter to be delivered to faculty to begin a private discussion regarding your specific needs in a course. You may request accommodations at any time, however, ODA notices of accommodation should be provided as early as possible in the semester to avoid any delay in implementation. Note that students must obtain a new letter of accommodation for every semester and must meet with each faculty member prior to implementation in each class. For additional information see the Office of Disability Accommodation website at http://www.unt.edu/oda. You may also contact them by phone at 940.565.4323.