Download Syllabus

Statistical Methods STAT 2303
Fall 2011
Course Title
Statistical Methods
Prerequisites
No previous knowledge is requested.
Instructor
Professor Mohamed I Riffi,
Office Location: C729, Tel. 2611
e-mail: [email protected] or [email protected]
Office Hours
Saturday/Monday/Wednesday 11:00 – 12:00 or by appointment.
Make-up policy
Make-up tests will be given only to students absent for legitimate reasons. If you
know in advance that you will miss a test date, please let me know as soon as
possible.
Homework
Most of the homework I ask you to do will be “suggested” homework, which will not
be taken up or graded. However, many test questions will be similar to the
suggested homework --- so you should do the suggested homework.
Required Materials:
OpenIntro Statistics, 3rd Edition, by David M Diez, Christopher D Barr, and Mine C_
etinkaya-Rundel.
Free electronic copy: https://www.openintro.org/stat/textbook.php?stat_book=os
References
1. Statistical Methods, 2nd Edition, by Rudolf J. Freund and William J. Wilson.
2. Statistics: Informed Decisions Using Data, by Michael Sullivan, III.
Course Content
Chapters one through eight will be covered in this course. Some sections of these
chapters will be omitted. The following topics will be covered: descriptive and
inferential statistics, graphical and numerical methods of describing data, normal
distributions, estimation, hypothesis testing, and linear regression and correlation.
Course objectives
In the course you will be introduced to some basic tools of statistics that will help
you organize, summarize, analyze, and draw conclusions from data. You will get
experience in applying these tools to conduct your own statistical study and in
presenting the results of your study in a professional manner. After successful
completion of this course the student will be able to:
1. Distinguish the use of descriptive statistics from the use of inferential
statistics.
2. Distinguish qualitative data from quantitative data.
3. Construct a frequency distribution, relative frequency distribution, and
cumulative frequency distribution for a given set of data.
4. Construct a histogram for a given set of data.
5. Compute and provide a qualitative interpretation for the mode, mean, and
median of a given set of data.
6. Compute and provide a qualitative interpretation for the range, interquartile
range, and standard deviation of a given data set.
7. Find the proportion of data between two given values for a normal
distribution.
8. Find the value of a given percentile for a normal distribution.
9. Compare scores from two different normal distributions using standard
scores.
10. Construct a scatter-plot for a given set of paired data.
11. Compute and provide a qualitative interpretation for the correlation coefficient
of a given set paired data.
12. Compute the slope and y-intercept of the least squares prediction line to
predict the value of variable from the value of the other.
13. Provide a strategy for collecting a random sample from a given population.
14. Compute and provide a qualitative interpretation for the mean of all sample
means and the standard error of the mean for a given population and sample
size.
15. Perform the six steps of hypothesis testing for a z-test, t-test, t-test for two
independent samples, and t-test for matched samples.
16. Distinguish Type I errors from Type II errors and provide a strategy for
minimizing the chance of one or the other occurring.
17. Find and provide a qualitative interpretation for a confidence interval.
18. Perform the six steps of hypothesis testing for a chi-square test.
19. Determine the appropriate hypothesis test to use in a given situation.
Types of Assessments, Course Polices and Determination of Your Grade
Your course grade will be based on midterm exams, quizzes, projects, and the final
exam according to the following table:
Activity Name
Description
Points
1st Mid-term Exam
Saturday 6/2/2016
15 pts
2nd Mid-term Exam
Saturday, 19/3/2016
15 pts
Project
Due Wednesday 18/5/2016
20 pts
Final
Comprehensive
50 pts
Total
100 pts
Projects
- I will provide you during this course with full information about how to prepare for
your project and do it.
- Every student must do his own project by himself.
- Late projects will not be accepted.