Probability and Statistics for Engineers ( STT 351)

STT 231 – 001

STATISTICS FOR SCIENTISTS

SPRING 2014

Instructor: Dr. Elijah DIKONG

Office: A501 Wells Hall

PHONE: 884-1486

E-mail:

Office Hours: MWF: 10:30A.M. – 12:00P.M. @ A501WELLS

Class Schedule: MW: 03:00 p.m. - 04:20 p.m. at 402 CC

Text: Statistics for Scientists (Course Pack) by V. Melfi

Class Website: http://www.stt.msu.edu [For class notes, homework assignments, handouts, etc.]

http://angel.msu.edu [Angel will be used only to post grades]

Course Objectives: This is a calculus based course in probability and statistics. Our goals will be to get basic understanding of concepts in probability and statistics and explore their applications to the sciences.

Quizzes: There will be two (2) quizzes throughout the semester. Each quiz will last 30 minutes. The maximum number of points for the quizzes is 50. Make up quizzes will not be given for any reason. The class will be reminded one week in advance prior to a quiz date in class, and through email. The tentative dates for the quizzes are:

Quiz Number 1: Monday January 27, 2014;

Quiz Number 2: Wednesday March 12, 2014;

Homework: There will be 2 Homework Assignments worth 50 points each that will be given as we cover the corresponding material. Homework Assignments must be turned in on time. Late submissions are subject to a 20% point reduction. Homework Assignments submitted two days after the due date would not be accepted. Some of the homework exercises will have elements of a project exercise. You may work in groups of up to 6 students on the homework. If you work in a group, you may turn in one homework assignment for the whole group (make sure all group member’s names and PIDs are clearly written on the assignment cover page; see sample cover page below). In addition, some reading and suggested homework problems from the text will be assigned. These problems will not be collected. However, it is essential that you work them out.

Projects: There will be two (2) in – class projects. Each project is worth 25 points. Depending on the nature of the project, you will be required to bring pencils, markers, erasers, TI calculators, etc. On a project day, students work in assigned course groups of maximum six (6) students. The tentative project schedule dates are:

In – class project 1: Wednesday February 12, 2014

In – class project 2: Monday April 21, 2014

Tests: There will be three in-class multiple - choice tests worth 100 points each given during the semester. Test questions will be asked based on concepts covered in lecture, homework problems, and the examples worked out in the class. The following is a tentative list of test dates:

Test Number 1: Monday February 10, 2014;

Test Number 2: Wednesday March 19, 2014;

Test Number 3: Monday April 14, 2014.

Final Examination: There will be a cumulative final examination at the end of the semester. The final examination is worth 200 points. Though the final examination is cumulative, it is weighted as follows: Topics On Statistical Inferences > Topics On General Probability > Topics On Descriptive Statistics.

The final examination is scheduled on MONDAY APRIL 28, 2014. The duration of the final examination is two (2) hours, starting at 3:00 p.m. and ending at 5:00 p.m. The final examination venue is 402 CC.

Extra Credit Problems: (i) Optional extra credit problems will be given in class on a regular basis. I will most likely assign extra credit problems on Wednesdays, and they will be due the following Monday. Each extra credit point is worth 1/10 of a test point. For example, if you have earned a total of 25 points from extra credit problems, then 2.5 points will be added to your total score. I will not return graded extra-credit work. The material will be used for research purposes. You will be constantly informed though of your extra-credit points accumulated.

(ii) Throughout the semester, I will give an undetermined number of unannounced quizzes. These quizzes are designed to give your instructor better feel of how much you understand of the concepts disseminated and also to help you curve your grade for the class. Unannounced quizzes are given ten minutes to the end of lecture and are based on the concepts discussed that day in class.

An Important Remark On Extra Credit Policy: As a consequence of the many extra credit opportunities offered during the entire semester, numeric grades will not be rounded up even if a student is short of 0.5 points to earn a higher grade. For example, to earn a numeric grade of 4.0, a student must have earned a total of at least 630 points of the possible 700 points. If such a student’s total score at the end of the semester is 629.5 points out of the possible 700 points, he or she earns a numeric grade of 3.5. I will not respond to emails at the end of the semester begging me to round up grades. To avoid this, you are strongly encouraged to take maximum advantage of the extra credit opportunities that will be available to you throughout the semester. In this way, you will continually curve your class grade up during the semester.

Remark: If you are unable to take an examination for a legitimate reason, you must contact the instructor on or before the day of the examination. You must justify your absence before you are allowed to take a make-up examination. You cannot take a make-up examination just because you are not ready for the examination, or it is your birthday, or you are to attend a wedding ceremony, or for some other ‘lame’ reason.

Course Grade: The total (possible) number of points earned for STT 231 - 001:

Your course average is computed by taking the sum of marks of your 2 Quizzes, 3 Tests, 2 Homework Assignments, 2 In-class Projects, and Final Examination Scores. The grading scale will be as follows:

Percentage Numeric Grade Points Range

90 - 100% 4.0 630 - 700

85 – 89.9% 3.5 595 – 629

79 – 84.9% 3.0 553 – 594

73 – 78.9% 2.5 511 – 552

65 – 72.9% 2.0 455 – 510

60 – 64.9% 1.5 420 – 454

55 – 59.9% 1.0 385 – 419

00 – 54.9% 0.0 000 - 384

Reminder: Grades are not curved or adjusted. This is not to dishearten students, but to let them know that their grades are based on individual effort and not on comparative effort. By taking advantage of the extra-credit policy, you can curve your grade throughout the semester.

Important Dates:

January 06: First day of classes.

January 10: Close of add period.

January 20: Martin Lurther King Day (No classes)

January 31: Last Day for 100% refund

February 26: Middle of semester; last day to drop with no grade assigned

March 03 - 07: SPRING BREAK!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

April 25: Last Day of Classes

April 28: Final Examination at 402 CC

Time: 3:00 P.M. – 5:00 P.M.

Attendance: I recognize that students have busy lives and may have to miss some lectures. There is no explicit penalty for missing lecture, but you are responsible for learning the course material that you missed. A friend’s notes are a good place to start. That said, I will take attendance each class meeting and will compensate all those who attend lectures over 90% of the time, by adding 5 extra points to their semester total points.

Courtesy: With a large class size, courtesy is extremely important in maintaining an effective learning environment. Here are some rules to follow.

·  If you must arrive late or leave a lecture early, please do so in a way that does not disrupt the lecture for others. In particular, choose a seat near to the exit.

·  Do not talk in class unless you are asking the instructor a question or responding to a question asked by the instructor. In particular, even quiet conversation with your neighbor cannot occur.

·  Cell phones, pages, and other noise-making devices must be turned off. If you must be reached in an emergency, use a silent setting on your phone or pager.

Academic Honesty: The Department of Statistics and Probability adheres to the policies of academic honesty as specified in the General Student Regulations 1.0, Protection of Scholarship and Grades, and in the all-University of Integrity of Scholarship and Grades, which are included in Spartan Life: Student Handbook and Resource Guide. Students who plagiarize may receive a 0.0 on the assignment or fail the course.

ADA: To arrange for accommodation, students with disabilities should contact the Resource Center for People with Disabilities. Telephone: 355-9642; Website: http://www.rcpd.msu.edu

Advice for Students: DON’T FALL BEHIND! This class moves at a rapid pace.

·  Come to class prepared.

(i)  Read the chapter before lecture.

(ii)  Reread the chapter after lecture to see if you have follow up questions.

(iii)  Do the suggested exercises and visit my office hours or the statistics help room at A102 Wells if you have any questions.

·  Form a study group.

·  Learn how to use your calculator (Go to the statistics help room, A102 Wells for assistance on how to use your calculator.)

·  Keep a list of reference examples.

·  Do not hesitate to get help if you need it from the professor or the teaching assistants at the Statistics Help Room.

MORE ON STUDENT CONDUCT

·  The instructor has the responsibility to teach. Students have the right to learn. Everyone needs to be respectful of the rights of other people in the class.

·  Please avoid frequent tardiness. Arriving late and/or leaving early is not acceptable.

·  Disruptive behavior which impedes the teaching/learning process will not be tolerated – use of cell phones, audio devices (except tape recorders used to record), and abusive language are prohibited.

·  Discussion is encouraged in my classroom. However, please be respectful when the instructor or other students are speaking: listen attentively, disagree politely, and at all times avoid ridiculing others. Finding mistakes in my lectures is, however, encouraged, and is part of the fun.

·  Talking or whispering during lectures or presentations is not acceptable.

·  Michigan State University policies regarding harassment will be enforced.

·  Class lasts entire period. Do not begin packing up or repeatedly checking the clock (indicating your impatience) before class is dismissed.

·  Any form of cheating is considered a serious offense and will be dealt with according to Michigan State University guidelines. All persons involved are considered responsible, including the person from whom others copy. Thus it is your responsibility to place your materials in such a way that others will not have an opportunity to copy them. You may be asked to sit in specific seats so as to spread out examination takers.

DESCRIPTION OF UNITS

Unit 1: Descriptive Statistics (Week 1 – Week 6)

·  Data as collected information with its context;

·  Displaying and summarizing quantitative data – histograms, simple stem-and-leaf displays; Shape of a distribution (center, symmetry, spread, outliers, 5 – number summary);

·  Understanding and comparing distributions: 5 – number summary and boxplots; comparing groups with histograms, comparing groups with boxplots;

·  Exploring relationships between variables – scatter plots (Course Pack Chapter 4)

·  Linear regression models: Computing least squares lines (Course Pack Chapter 5)

·  Linear regression models: Prediction, residual, and influential points (Course Pack Chapter 6);

·  Linear regression models: Coefficient of determination, correlation coefficient, interpretation in liner models (Course Pack Chapter 7);

·  Estimating population size: Capture – Recapture Method (Course Pack Chapter 8) (Project or class activity);

Unit 2: General Probability (Week 7 – Week 11)

·  Probability Models: Finitely many outcomes; Events; Combining events; Assigning and interpreting probabilities (Course Pack Chapter 9)

·  Conditional Probability and Tree Diagrams (Course Pack Chapters 10 and 11);

·  Discrete Probability Distributions: Geometric, Binomial, Hypergeometric distributions (Course Pack Chapters 13, 14, and 15)

·  Mean, Variance, Standard Deviation of Discrete Probability Distributions (Course Pack Chapter 22)

·  Independence and Joint Distributions (Course Pack Chapter 12)

·  Continuous Random Variables and Continuous Probability Distributions: Density functions – uniform densities, exponential densities, the standard normal densities, computing probabilities and percentiles (Course Pack Chapters 19, 20, 21)

Unit 3: Statistical Inferences (Week 12 – Week 17)

·  Sampling distributions for proportions and means: The central limit theorem (Course Pack Chapter 24);

·  Confidence Intervals for proportions and means (Course Pack Chapters 25, 26, 27)

·  Hypotheses Testing for Proportions and Means: Test statistics, P – values, Type I and II Errors, Power of a test (Course Pack Chapters 17, 18)

Extra Credit Work #1 (EC#1)

Read Course Pack Chapters 1 and 2. Do exercises 2.9, Nos. 1, 4, and 5. Your work must be typed. Un-typed work will not be accepted. The due date for EC#1 is Wednesday January 15, 2014.