COURSE INFORMATION
Course Title: STATISTICS II
Code Course Type Regular Semester Lecture Recit. Lab Credits ECTS
BUS 202 A 4 - - - 4 5
Lecturer and Office Hours: Abdulmenaf Sejdini
Teaching Assistant(s) and Office Hours: -
Language: English
Compulsory/Elective: Compulsory
Classroom and Meeting Time: N/A
Course Description: Statistics II: The aim of the courses is that inference making in Business. The objective of the course is to help students to understand theoretical characteristics of statistical methods and develop practical knowledge and skills to analyze the business data.
Course Objectives: Theory of statistics and its application in business decision making. Since this is the continuation of the course of Statistics I the objective is to teach students hypothesis testing, comparisons of mean, experimental design, ANOVA, and all of the details of the simple linear regression. In order to increase the teaching and learning level the above topics will be taught from theoretical and practical aspects that would include teaching with appropriate exercise for every concept and statistical software laboratory as well as a practical case study for each chapter that is aimed to be covered.
COURSE OUTLINE
Week Topics
1 Hypothesis testing – developing null and alternative hypothesis; type I and Type II errors (ch 9)
2 Hypothesis testing – Population mean with a known standard deviation; population mean with an unknown standard deviation; population proportion (ch 9 continued)
3 Application: exercises; case studies assignment and laboratory for ch 9.
4 Comparisons involving means, experimental design, and analysis of variance(ANOVA)- inference about the difference between two population means and matched samples; (chapter 10)
5 Comparisons involving means, experimental design, and analysis of variance(ANOVA)- experimental design and ANOVA)(chapter 10)
6 Application: exercises; case studies assignment and laboratory for ch 10.
7 They become proficient in basic inferential statistical data analysis.
8 Test of Independence ( ch 11 Continued)
9 Mid-term
10 Application: exercises; case studies assignment and laboratory for ch 11
11 Simple Linear regression and least squares method (ch 12)
12 Simple Linear regression coefficient of determination and testing for significance (ch 12 continued)
13 Simple Linear regression , point and interval estimation and residual analysis (ch 12 continued)
14 Review Session and Application: case studies submission and presentation
Prerequisite(s): -
Textbook: Essentials of Statistics for Business and Economics, 6th Edition David R. Anderson; Dennis J. Sweeney; Thomas A. Williams; Jeffrey D. Camm; James J. Cochran, 2011
Other References: -
Laboratory Work: N/A
Computer Usage: N/A
Others: No
COURSE LEARNING OUTCOMES
1 To understand and apply the concept of hypothesis testing which includes developing and interpreting the results of the hypothesis testing.
2 To understand and be able to make comparisons between means, experimental design and analysis of variance
3 To understand and be able to make comparisons involving proportions and test of independence
4 To understand and be able to do simple linear regression and all of its analysis techniques
5 All of the above mentioned topics and objective to be applied through practical case studies by using the corresponding statistical software.
COURSE CONTRIBUTION TO... PROGRAM COMPETENCIES
(Blank : no contribution, 1: least contribution ... 5: highest contribution)
No Program Competencies Cont.
COURSE EVALUATION METHOD
Method Quantity Percentage
Midterm Exam(s)
1
30
Quiz
2
5
Laboratory
1
5
Case Study
3
5
Final Exam
1
35
Attendance
5
Total Percent: 100%
ECTS (ALLOCATED BASED ON STUDENT WORKLOAD)
Activities Quantity Duration(Hours) Total Workload(Hours)
Course Duration (Including the exam week: 16x Total course hours) 16 3 48
Hours for off-the-classroom study (Pre-study, practice) 16 2 32
Mid-terms 1 21 21
Assignments
Final examination 1 10 10
Other 1 14 14
Total Work Load:
125
Total Work Load/25(h):
5
ECTS Credit of the Course:
5