Applied Statistics II- Winter 2016

Meeting Times:

Email:

Meeting Location: 2046CB

Office: 2087CB

Monday 10:30 AM- 12:00PM

Wednesday 5:00 PM- 6:00PM

Friday 10:30 AM- 12:00PM

and by appointments

- Test Hypothesis for the diffrence between two population means
- Find diffrence between two population meand: paired differences
- Estimate coefficients of fitted line
- Fit regression model using Qualitative and quantitative variables
- Calculate goodness of fit test for categorical data
- Use distribution free tests: nonparametric tests

- Peck, Olsen, and Devore (2012). Introduction to Statistics & Data Analysis. 4th Edition. Publisher: Duxbury.
- Diez, Barr, and Cetinkaya-Rundel,
**OpenIntro Statistics.** - McClave and Sincich (2012). Statistics, 12th edition, by Pearson.

At least five sets of homework problems will be assigned. Some addition homework problems will periodically be assigned during the lecture. Good news! lowest homework grade will be dropped. For better exam results you need to master all the homework problems. The single most important part of this course is doing your homework and review questions.

There will be two mid-term exams, and a comprehensive final. To answer the exam questions, you are expected to have clear mathematical reasoning of the statistical methods used to solve the subject problem.

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.

We will use a software called "R". R is a programming language for statistical computing and visualizing data. It can be downloaded for free from http://www.r-project.org. We will R Studio for regular classroom activities. R studio is an open source Integrated development Environment(IDE) for R. To download R click

Evaluations/Important Dates: | ||

Exam I (20%) | Monday, February 15 | |

Exam II (20%) | Monday, April 04 | |

Mini Project I(10%): | Due Feb 24 | |

Mini Project II(10%): | Due April 13 | |

Homeworks (15%) | TBD | |

Final Exam (25%) | Monday, April 25(3:00PM-6:00PM) |

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 |

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 including 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

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

Date | Sections | Topics covered | Remarks |

January 6 | Review of Confidence Interval | ||

January 11 | 9.3 | A large-sample test about population mean | Rlab |

January 13 | 9.4 | Difference between population means | |

January 18 | No class | MLK DAY | |

January 20 | 10.3,10.4 | Small -sample inference: independent sample test | |

January 25 | 10.4. 10.5 | Small -sample inference: independent and paired-difference test | |

January 27 | 10.6, 10.7 | Comparing two population variances | |

February 1 | 11.1-11.4 | Introduction: Analysis of Variance | |

February 3 | 11.5 | Completely randomized design | |

February 8 | 11.7 | Randomized block design | |

February 10 | 11.8 | ANOVA for a randomized block design | |

February 15 | Exam 1 | ||

February 17 | 11.10 | Factorial experiment | |

February 22 | 12.1-12.4 | Linear regression | |

February 24 | 12.5 | The coefficient of determination | |

February 29- March 04 | Break | ||

March 07 | 12.6 | Estimationa and prediction using the fitted line | |

March 09 | 13.1-13.3 | Multiple linear regression | |

March 14 | 13.4 | Polynomial regression model | |

March 16 | 13.5 | Qualitative predictor variables in a regression | |

March 21 | 13.6 | Testing and training sets of regression coefficients | |

March 23 | 14.1-14.3 | Goodness of fit-test | |

March 28 | 14.4 | A two-way classification | |

March 29 | 14.5 | Comparing several multinomial populations | |

April 4 | Exam 2 | ||

April 6 | 15.1-15.3 | The wilcoxon rank sum test | |

April 11 | 15.5 | The wilcoxon rank sum test: paired experiment | |

April 13 | 15.6 | Kruskal-Wallis test | |

April 18 | Review | ||

April 25 | Final Exam (3:00AM- 6:00 PM) |

| Description | Remarks |

Ex 9.3 : 9.1, 9.3, 9.4, 9.6, 9.8, 9.15, 9.16 Ex 9.4: 9.18, 9.22, 9.28 | Due Jan 25 | |

Ex 9.5: 9.31, 9.35, 9.38, 9.41 9.42, 9.45, 9.50, 9.51 | Due Wed Feb 03 | |

Ex9.6: 9.42, 9.46 Ex 10.3: 10.2, 10.3, 10.6 Ex 10.4: 10.18, 10.19, 10.27, 10.30 Ex 10.5: 10.36, 10.41, 10.46 | Wed, feb 10th | |

Ex 10.6: 10.49, 10.51, 10.53, 10.55, 10.56 Ex 10.7: 10.58, 10.10.59, 10.61, 10.10.63, 10.66 | Exam 1 covers up to section 10.7 | |

Ex 11.5:: 11.1, 11.2, 11.7,11.12, 11.1411.18 Ex11.8:: 11.28, 11.33, 11.36, 11.37,11.4011.43 Ex11.10:: 11.45, 11.49, 11.5011.52 | Quiz from exercise 11.5 on Match 07th. | |

Ex 12.4:: 12.1, 12.3, 12.7, 12.9, 12.12, 12.15, Ex12.5:: 12.19, 12.20, 12.23, 12.24, 12.28, 12.30 Ex12.6 :: 12.34, 12.36, 12.38 EX12.7:: 12.40, 12.42, 12.44, 12.45, 12.46 | Quiz on march 16th and HW Due March 16th | |

Ex 13.4: 13.1, 13.3, 13.5, 13.10, 13.12, 13.15 ExEx13.5: 13.17, 13.18, 13.20, 13.22, 13.24 | this will be a part of exam 2 |

| Description | Remarks |

review: Hypothesis Testing | ||

Data Visualization | ||

Measures of Data | ||

Normal Distribution | ||

Central Limit Theorem | ||

Book Data | Download |

Exploratory Data Analysis Wide range of statistical topics are covered in this web page with video lectures and other supplementary materials.

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