Introduction to Statistics- Fall 2017

#### Meeting Information

Instructor: Keshav P. Pokhrel, Ph.D.
Meeting Times: TTR 3:30PM- 4:45PM
Email: kpokhrel(at)umich.edu
Meeting Location: 2046 CB
Office: 2087CB
Office Hours:
Monday 12:30 PM-1:30 PM
Tuesday 12:30 PM- 1:30 PM
Thursday 5:00 PM- 5:50 PM
and by appointments.

#### Course Description

This course is primarily designed for those who want to apply quantotative resoaing in different areas social and natural sciences. After a completion of this course, students are expected to make and informed inferential analysis. Topics covered include: Frequency distributions, descriptive measures, sampling, and statistical inference, elementary probability theory, linear regression, and use of statistical computer packages to analyze data.

#### Course Objectives:

Upon successful completion of the course, the students should be able to:
1. Demonstrate understanding of the following statistical concepts: Descriptive statistics, sampling distribution, normal distribution, confidence intervals, hypothesis testing, and linear regression.
2. Recognize the use and misuse of statistics in real life situations, in the news, and surveys.
3. Visualize the data using statistical techniques.
4. Explore the concepts of basic probability theory in decision making processes.

#### Dearborn Discovery Goals:

• Critical and Creative Thinking

#### Program Goals:

• Statistics Program Goal

#### Textbook

Elementary Statistics: Picturing the World 6th edition, Larson Ron and Farber Besty, 2012; ISBN: View Larger Image 9780321911216, Prentice-Hall. We will be cover chapters 1, 2, 3, 5, 6, 7, 8 ,9 and 10*.

#### Homework

Homework problems from each chapter will be assigned through Mystatlab . Some additional homework problems will periodically be assigned during the lecture. For better in class quiz/exam results you need to master all the homework problems. I strongly encourage you to see me for help if you are unable to solve the assigned problems. You are expected to spend an average of 3-5 hours of work per week outside of class. Late assignment is accepted with 20% penalty per day. For better exam results you need to master all the homework problems.

#### Exams

There will be two mid-term exams, and a final exam. To answer the exam questions, you are expected to have clear idea to interpret the numerical outputs of the statistical methods.

#### In Class Work and Quizzes

You will get worksheets with problems in the class. Students can interact with the friends and look at the notes to solve the problems. I encourage everyone to solve the problems on the white board and interpret the results to the class. I urge you to find interesting problems from the areas (eg. business, sociology, biology, sports, public health etc.) of your interest, this will help you to prepare for your project and at the same you are higly likely to earn better score in quizzes.

#### Project

There will be two mini-projects during the semester. For a good project, you need to describe the data, pose reasonable hypotheses, select appropriate statistical tests, compute the test results, and explain the results in both statistical terms and in plain English. Primary objective of these projects is to apply statistical methods in the real life situations and encourage students to work in a group. Late submission of project will result in losing 10% of total points everyday.

#### Software

 Important Dates: Exam I Tuesday, October 10 Exam II Tuesday, November 21 Group project part I (5%): Due October 31 Group project part II(5%): Due December 05 Final Exam Thursday, Dec 14(3:00 PM-6:00PM)

#### Evaluations:

Your performance is measured by the weighted average of two in class exams, homework, in-class work, group project and a final exam. If you have any grade disputes you need to notify me within a week after grades are posted in canvas.
• (40%)- Two Mid-Term Exams
• (15%) - homework
• (10%) - classwork/quizzes
• (10%) - group project
• (25%)- Final Exam
 Letter Grade E D- D D+ C- C C+ B- B B+ A- A A+ Percentage 0-59 60-62 63-66 67-69 70-72 73-76 77-79 80-82 83-86 87-89 90-92 93-96 97-100

#### Disability Statement

The University will make reasonable accommodations for persons with documented disabilities. Student need to register with Disability Resource Services (DSR) every semester they are enrolled for classes. DRS is located in counseling & Support Services, 2157 UC. To be assured of having services when they are needed, students should register no later than the end of add/ drop deadline of each term. Visit the DSR website at: webapps.umd.umich.edu/aim. If you have disability that necessitates an accommodation or adjustment to the academic requirements stated in this syllabus, you must register with DRS as directed above and notify me. Upon receipt of your notification, we will make accommodation as directed by DRS.

￼The University of Michigan-Dearborn values academic honesty and integrity. Each student has a responsibility to understand, accept, and comply with the University,s standards of academic conduct as set forth by the Code of Academic Conduct ￼(mdearborn.edu/policies_st-rights), as well as policies established by each college. Cheating , collusion, misconduct, fabrication, and plagiarism are considered serious offenses, and may be monitored using tools including but not limited to TurnItIn. Violations can result in penalties up to and includiing expulsion from the University. At the instructor,s direction, the penalty may be a grade zero on the assignment up to and including recommending that student be expelled from the University. It is the sole responsibility of the student to understand and follow academic guidelines regarding plagiarism. The University of Michigan-Dearborm has an online academic integrity tutorial that can be accessed at: umdearborn.edu/umemergencyalert

#### Safety

All students are strongly encouraged to register in the campus Emergency Alert System, used to communicate with campus community during emergency. More information on the system and how it works, along with enrollment information can be found at: webapps.umd.umich.edu/aim

 Week Chapters/Sections Topics covered Remarks Week 1(Sept 7) Chapter 1 (sections 1.1, 1.2) Introduction to Statistics Week 2(Sept 12, 14) Chapter 1 (sections: 2.1-2.5) Descriptive Statistics Week 3(Sept 19, 21) Chapter 3 (sections: 3.1-3.3) Basic concepts of probability Week 4 (Sept 26, 28) Chapter 5 (sections: 5.3-5.4) Central Limit Theorem Week 5 ( Oct 3, 5) Chapter 6 , review (sections 6.1) Confidence Intervals Week 6,7 (Oct 10, 12, 19) Exam I, Chapter 6 (sections 6.2-6.4) Week 8 ( Oct 24, 26) Chapter 7(section: 7.1-7.3) Hypothesis Testing (one Sample) Week 9( Oct 31, Nov 2) Chapter 8 (section: 8.1-8.3) Hypothesis testing(Two Samples) Week 10 (Nov 7,9) Chapter 9 (section: 9.1-9.2) Correlation and regression Week 11, 12 (Nov 14, 16, 21) Chapter 9 (section: 9.3); Review ; Exam II Measures of linear regression Week 13 (Nov 28, 30) Chapter 9 (section: 9.4) Multiple Linear Regression Week 14 (Dec 5, 7) Chapter 4, Chapter 10 (4.2, 10.1) Binomial Distribution, Goodness of Fit test Week 15(Dec 12) Chapter 10 (section: 10.2) Test of Independence

### Selected Practice Problems

 Section Selected Problems Remarks 2.1 7,8, 9, 10,15, 18, 19,21, 24, 25, 28, 33, 35, 40, 47 2.2 3, 5, 7, 10, 12, 13, 14, 15, 19, 30, 32, 34 2.3 5, 7, 8,10, 12, 14, 17, 18, 19, 22, 24, 29, 32, 35, 38, 40, 41, 42, 44, 47, 49, 52, 55, 58 2.4 5, 8,11, 14, 15, 16, 19, 20, 29, 31 2.5 1, 3, 5, 7, 10, 13, 14, 21, 30, 35, 36, 39, 40, 42, 44, 48, 50 4.1 1, 3, 5, 8, 9, 12, 13, 15, 17, 20, 22, 25, 27 4.2* 1, 2, 3, 7-10, 11, 14, 15, 16, 18, 20, 27, 30, 32 5.1 1, 3, 4, 6, 10, 11, 12, 14, 19, 20, 22, 24, 25, 26, 29, 30, 33, 37,39, 43, 45-50, 51, 54, 56 5.2 1, 4, 6, 7, 11, 13, 15, 16, 17, 20 5.3 1, 7, 11, 15, 16, 19, 20, 22, 24, 27, 31, 33, 34, 35, 37 5.4 1, 7, 9, 10, 13, 15, 18, 22, 24, 25, 27, 31, 33, 35, 37, 38 6.1 1, 3, 5, 9, 12, 17, 21, 23, 25, 28, 32, 35, 37, 39, 43, 46, 50, 54 6.2 1, 4, 6, 8, 9, 12, 17, 20, 27, 29 6.3 1, 2, 4, 6, 11, 13, 15, 18, 20 7.1 1, 2, 5, 7, 10, 21, 23, 24, 27, 29, 33, 37, 40, 43, 46, 49, 50, 51 7.2 1, 2, 3, 6, 8, 11, 14, 17, 20, 22, 23, 27, 28, 29 7.3 1, 3, 6, 8, 9, 13, 15, 16, 18, 21, 25 7.4 3,6,8, 10, 11, 12, 14, 25, 16, 17 8.1 1, 4, 7, 9, 10, 13, 16, 17, 18, 21 8.2 3, 5, 6, 9, 11, 13, 15, 17 8.3 3, 4, 6, 9, 11, 13, 19 9.1 1-18, 22, 24, 27, 29, 30 9.2 7, 8, 9, 11, 12, 17, 19, 20, 22, 24, 30, 31 9.3 1, 2, 4, 5, 7, 12, 13, 15, 16, 17, 18 10.1 3, 6, 8, 10, 15, 17 10.1 7,8, 10, 13, 17, 18, 21, 22

### Extra Resources

StatSci.org. A good resource for varieties of data sets. These data sets are open to public and you can use these data sets for your own projects. If you happen to use these data please do not forget to mention the source.
Online Statistics Education This a very helpful resource for introductory statistics.
Distribution Calculator An excellent Apps to understand binomial distribution normal approximation to binomial
Exploratory Data Analysis Wide range of statistical topics are covered in this web page with video lectures and other supplementary materials.
Unlocking the power of data a very rich resource for introductory statistics with apps.
Why to study Statistics? Applications of Statistics in different areas of study.