Course Name
Code
Semester
Theory
(hour/week)
Application/Laboratory
(hour/week)
Local Credits
ECTS
Introduction to Probability and Statistics II
MATH 212
Fall/Spring
3
0
3
5

Prerequisites
  MATH 211 To attend the classes (To enrol for the course and get a grade other than NA or W)

Course Language
English
Course Type
Service Course
Course Level
First Cycle
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives To provide the fundamental concepts of Probability and Statistics with applications of business and economic problems. The course illustrates many examples of common statistical methods for students who would like to focus on information intensive fields.
Course Learning Outcomes The students who succeeded in this course;
  • will be able to compute confidence intervals for the mean of one and two populations that are normally distributed when the population variance is known and population variance is unknown.
  • will be able to apply hypotesis tests for the mean of a population or between two populations that are normally distributed when the population variance is known and population variance is unknown.
  • will be able to identify the dependent and the independent variables of the given data and to conclude whether given variables are related or not
  • will be able to apply simple or multiple linear regression analysis
Course Content Sampling distributions, Confidence interval estimation: one and two populations, Hypothesis Tests of one and two populations, Simple and multiple regression analysis

 

Week Subjects Related Preparation
1 Sampling distributions: distributions of the sample mean and sample proportions Statistics and Business Economics by P. Newbold W. L. Carlson, B. Thorne, 8/e, Prentice Hall: 6.1-6.2 (244:264)
2 Sampling distributions: distributions of the sample variance. Statistics and Business Economics by P. Newbold W. L. Carlson, B. Thorne, 8/e, Prentice Hall: 6.3-6.4 (265:283)
3 Confidence interval estimation for the mean of a normal distribution when the population variance is known and when it is unknown. Statistics and Business Economics by P. Newbold W. L. Carlson, B. Thorne, 8/e, Prentice Hall: 7.1-7.3 (284:302)
4 Confidence interval estimation for population proportions and population variance. Sample size determination. Statistics and Business Economics by P. Newbold W. L. Carlson, B. Thorne, 8/e, Prentice Hall: 7.4-7.8 (303:327)
5 Confidence interval estimation of the difference between two normal population means: dependent and independent samples. Confidence interval estimation of the difference between two population proportions. Statistics and Business Economics by P. Newbold W. L. Carlson, B. Thorne, 8/e, Prentice Hall: 8.1-8.3 (328:345)
6 Concepts of hypothesis testing. Hypothesis test of the mean of a normal distribution when the population variance is known. Statistics and Business Economics by P. Newbold W. L. Carlson, B. Thorne, 8/e, Prentice Hall: 9.1,9.2 (346:361)
7 Hypothesis test of the mean of a normal distribution when the population variance is unknown. Tests of the population proportion. Statistics and Business Economics by P. Newbold W. L. Carlson, B. Thorne, 8/e, Prentice Hall: 9.3,9.4 (385:398)
8 Hypothesis test of the difference between two normal population means for dependent and independent samples. Tests of the difference between two population proportions. Statistics and Business Economics by P. Newbold W. L. Carlson, B. Thorne, 8/e, Prentice Hall: 10.1-10.3 (385:402)
9 Linear models, Least squares regression technique. Linear Regression model. Statistics and Business Economics by P. Newbold W. L. Carlson, B. Thorne, 8/e, Prentice Hall: 11.1,11.2 (417:426)
10 Least squares coefficient estimators. The explanatory power of a linear Regression equation, Analysis of variance. Coefficient of determination. Statistics and Business Economics by P. Newbold W. L. Carlson, B. Thorne, 8/e, Prentice Hall: 11.3,11.4 (427:437)
11 Hypothesis test and confidence intervals for the population regression slope. Hypothesis test for the population slope using F distribution. Forecast and Prediction intervals. Statistics and Business Economics by P. Newbold W. L. Carlson, B. Thorne, 8/e, Prentice Hall: 11.5,11.6 (438:451)
12 Correlation analysis with hypothesis test for correlation. Statistics and Business Economics by P. Newbold W. L. Carlson, B. Thorne, 8/e, Prentice Hall: 11.7 (452:455)
13 The multiple regression model. Least squares estimation and sample multiple regression. The explanatory power of a multiple regression equation. Adjusted coefficient of determination and coefficient of multiple correlation. Statistics and Business Economics by P. Newbold W. L. Carlson, B. Thorne, 8/e, Prentice Hall: 12.1,12.2, 12.3 (473:492)
14 Confidence intervals and hypothesis tests for individual regression coefficients. Test on all coefficients of a multiple regression equation using F distribution Statistics and Business Economics by P. Newbold W. L. Carlson, B. Thorne, 8/e, Prentice Hall: 12.4,12.5 (493:510)
15 Review of the semester
16 Review of the semester

 

Course Notes / Textbooks Statistics and Business Economics by P. Newbold W. L. Carlson, B. Thorne; 8/e, Prentice Hall . Chapters 6,7,8,9,10,11,12.
References Essentials of Contemporary Business statistics by T.A. Williams, D.J. Sweeney, D.R. Anderson,2007, Thomson

 

Semester Requirements Number Percentage of Grade
Attendance/Participation
-
-
Laboratory
-
-
Application
-
-
Field Work
-
-
Special Course Internship (Work Placement)
-
-
Quizzes/Studio Critics
5
5
Homework Assignments
-
-
Presentation/Jury
-
-
Project
-
-
Seminar/Workshop
-
-
Midterms/Oral Exams
2
60
Final/Oral Exam
1
35
Total
8
100

PERCENTAGE OF SEMESTER WORK
-
65
PERCENTAGE OF FINAL WORK
-
35
Total 0 100

 

Course Category

Core Courses
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

 

#
Program Qualifications / Outcomes
* Level of Contribution
1
2
3
4
5
1

Adequate knowledge in Mathematics, Science and Computer Engineering; ability to use theoretical and applied information in these areas to model and solve Computer Engineering problems

2

Ability to identify, define, formulate, and solve complex Computer Engineering problems; ability to select and apply proper analysis and modeling methods for this purpose

3

Ability to design a complex computer based system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose

4

Ability to devise, select, and use modern techniques and tools needed for Computer Engineering practice

5

Ability to design and conduct experiments, gather data, analyze and interpret results for investigating Computer Engineering problems

6

Ability to work efficiently in Computer Engineering disciplinary and multi-disciplinary teams; ability to work individually

7

Ability to communicate effectively in Turkish, both orally and in writing; knowledge of a minimum of two foreign languages

8

Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself

9

Awareness of professional and ethical responsibility

10

Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development

11

Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of Computer Engineering solutions

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours)
16
3
48
Laboratory
-
-
-
Application
-
-
-
Special Course Internship (Work Placement)
-
-
-
Field Work
-
-
-
Study Hours Out of Class
15
2
30
Presentations / Seminar
-
-
-
Project
-
-
-
Homework Assignments
-
-
-
Quizzes
5
3
15
Midterms / Oral Exams
2
15
30
Final / Oral Exam
1
20
20
    Total Workload
143