MATH 260   

Introduction to Statistics
Spring 2018


 Until the phenomena of any branch of knowledge have been submitted to a measurement and number it cannot assume the status and dignity of a science” -Francis Galton




                                                 Example Set of Exams


Instructor:     Dilek Guvenc 

 Room: SA-105(Faculty of Science A-Block), ext: 2132
 E-mail :
 Office Hours:
  Tuesday 12:40-13:30 , Wednesday 10:40-11:30 and  Friday 14:40-15:30



 Class Schedule:

             Section 01         Wednesday          13:40 - 15:30         Room # FC-Z23D

                                       Friday                15:40 -16:30           Room # FC-Z23D

             Section 02         Monday             10:40 - 12:30          Room # B-204 

                                       Thursday           9:40 - 10:30            Room # B-204 

             Section 03        Tuesday             10:40 - 12:30           Room # B-204 

                                      Friday               9:40 -10:30               Room # B-204 


 Probability and Statistics for Engineers
 Richard  L. ScheafferMadhuri S. Mulekar, James T. McClave; 5-th Edition  Cengage Learning, 2011

Supplementary Textbook:

 Introduction to Probability  Theory and Statistical Inference
 Harold J. Larson,  John Wiley & Sons, 1982

 Exams & Grading :

       1st Midterm (27%)
                     Date:  March 9, 2018 ( Friday )
                     Time: 17:45

         2nd Midterm (27%)
                      Date:  April 12, 2018 ( Thursday )                                                                                                                                                                                                                                                          Time: 17:45

         Final Exam (34%)    Will be scheduled...

Attendance :   Attendance will be taken regularly.

      Homeworks ( 12% )    5 homeworks . Homeworks will be emailed on Monday of homework-weeks  (See syllabus below), they will be collected one week later and solutions of the homework questions will be emailed to the students.


·   Student will be qualified to take the final exam if his/her total is at least 20 over 66, by the last day of the classes.


·   Students who do not have least total score of 20 over 66 will be given an FZ grade.

·  Students who have missed a midterm exam and have valid, well-documented excuse can take a makeup of it. A single makeup exam will be given few days after the second midterm exam.

·    Reserved 4-th hour will be used in some weeks, this will be announced in the class.

§    Usage of a statistical software such as MINITAB  is encouraged.

· This course is not a regular math course! It involves qualitative thinking and more words than other mathematics courses. 

§   Following and understanding the lectures is necessary but not sufficient for understanding the material. The best way for that is to do more problems, especially "supplementary exercises" from the textbook.


            Syllabus:  (Tentative)

Week                            Subjects

1. Jan. 29       Tools for Describing Data.

2. Feb. 5       The Sampling Distribution of  Sample Mean, Sample Proportion and Sample Variance. 

3. Feb. 12       Point Estimators. Properties of Point Estimators. The Method of Maximum Likelihood. (Hw1) 

4. Feb. 19       Confidence Intervals: The Single-Sample Case, Prediction Intervals. 

5. Feb. 26     Confidence Intervals: The Multiple-Sample Case. (Hw 2)

6. March 5      Review, Applications & the First Midterm

                          (Friday, March 9, 2018 @ 17:45)

7. March 12    Hypothesis Testing: The Single-Sample Case 

8. March 19    Hypothesis Testing:  Multiple-Sample Case (Hw 3)  

9. March 26   Chi-Squared Tests on Frequency Data.

10. April 2    Chi-Squared Tests on Frequency Data (Cont.)  (Hw 4)

11. April 9     Review, Applications and the Second Midterm.

                                   (Thursday, April 12, 2018 @ 17:45)

12. April 16   Simple Regression. Probabilistic Models  Fitting the Model:  The Least-Squares Approach , The Probability Distribution of the Random Error Component. 

13. April 24     Making Inferences about the Slope . The Coefficient of  Correlation. The Coefficient of  Determination. Using the Model for Estimation and Prediction. Residual Analysis. Transformations. (Hw 5)       

14. May 2      Multiple Regression Analysis.

15. May 7     Multiple Regression Analysis Applications


&   FINALS...