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 Prof. Quintanilla |Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: | Department of Mathematics |Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: | University
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Math 3680.002: Spring 2014

Meets: MW 3:30-4:50 in Curry Hall, Room 203.

Instructor: Professor John Quintanilla

Office: GAB, Room 418-D

Office Phone: x4043

E-mail: jquintanilla@unt.edu

Web page: http://www.math.unt.edu/~johnq/Courses/2014spring/3680/

Office Hours: MW 12:30-2:30, 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.

Online Help: Click Ask Your Teacher near the top of each Enhanced WebAssign homework assignment and then follow the prompts.

Required Text: Probability & Statistics for Engineering and the Sciences, 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.

·         Bundle: Text + Enhanced WebAssign + Start Smart Guide for Students + Enhanced WebAssign Homework with eBook Printed Access Card for One Term Math and Science. ISBN 978-1-111-65549-5. Can be purchased for $186.99 from www.cengagebrain.com. Can also be purchased at the UNT Bookstore (price not available at this time).

·         eBook + Enhanced WebAssign. ISBN 978-1-285-85804-3. Can be purchased for $65 from www.cengagebrain.com.

Strongly Recommended: Lecture notes for the semester can be purchased from Eagle Images Print Center (located in the first floor of Stovall Hall; the front entrance of Stovall Hall faces Highland Street) for $18.95.

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

Please read the Enhanced WebAssign handout, distributed on the first day of class, for instructions about how to enroll yourself in the appropriate section of Math 3680. You will need the Class Key Code given at the top.

Click here for further instructions about getting started with Enhanced WebAssign.

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, January 17, with a bonus possible if submitted by January 15).

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

 

Date

Lecture

Notes

Textbook

Sections

Topic

YouTube

Review Videos

January 13

Lecture #1

1.2, 1.3, 1.4

Graphical Representation of Data

Page 3: Box and Whisker

Page 7: Histogram

January 15

Lecture #2

1.3, 1.4

Mean and Standard Deviation

Pages 2-3: Trimmed Means

Page 5: Mean and SD

January 20

UNIVERSITY CLOSED

January 22

Lecture #3

2.2, 2.4

Probability: Axioms and Multiplication Rule

Page 2: Probability

Page 5: Multiplication Rule

Page 7: Tree Diagram

January 27

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

January 29

Lecture #5

3.1, 3.2, 3.3

Discrete Random Variables and Probability Distributions

Page 2: Cumulative Distribution Function

Page 5: Mean and SD

February 3

Lecture #6

3.4, 3.5

Binomial and Hypergeometric Distributions

Pages 5-6: Binomial

Page 9: Hypergeometric

February 5

Lecture #7

4.1, 4.2

Continuous Random Variables

Page 2: Probability and Cumulative Distribution Function

Page 3: Percentile

Page 5: Mean and SD

February 10

Lecture #8

4.3

The Normal Distribution

Page 4: Probability

Page 5: Percentile

February 12

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

February 17

Lecture #9

4.3, 5.4

Approximating Binomial Distribution with the Normal Distribution

Page 4: Normal Approximation of Binomial Distribution

February 19

Lecture #10

4.6, 5.5

Probability Plots and Linear Combinations of Random Variables

Page 2: Probability Plot

February 24

Lecture #11

5.4

The Central Limit Theorem

Page 6: Estimating Probability Involving a Sum

February 26

Lecture #12

7.1, 7.2

Confidence Intervals: Large samples or known s

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

March 3

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

March 5

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

SPRING BREAK

March 17

Lecture #15

8.1

Introduction to Hypothesis Testing

To be added later

March 19

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.

March 24

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

March 26

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

March 31

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

April 2

Lecture #19

8.4

P-values

Page 1: Right-tailed z-Test

Page 5: Left-tailed t-Test

April 7

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

April 9

Lecture #21

9.2, 9.4

Two-Sample Data: Unpaired Small Samples and Proportions

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

Page 7: Hypothesis test for the difference of two proportions

April 14

Lecture #21A

9.3

Paired Data

 

The slides for this lecture can be found here; they were inadvertently omitted from the lecture notes.

To be added later

April 16

Lecture #22

12.5

Correlation

To be added later

April 21

Lecture #23

12.2, 13.2

Linear and Intrinsically Linear Regression

Page 8: Intrinsically Linear Regression: Percolation

 

Page 9: Intrinsically Linear Regression: Planets

April 23

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

April 28

Lecture #24

14.1, 14.3

The Chi-Squared Distribution

Page 8: Specified Proportions

Page 9: Testing Independence

April 30

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

May 7,

1:30-3:30 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

May 7, 1:30-3:30 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

The idea of this policy is that, if you are comfortably above the cut-off between grades at the time of the final exam, then you can receive the higher grade without taking the final. However, if you are too close to the cut-off, then you need to take the final to earn the higher grade.

·         I reserve the right to test and quiz you on problems which are generalizations of material covered in the class and/or in the text. In short, the problems may not look exactly like the ones in the book.


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.