COURSE INFORMATION Course Title: STATISTICS II

Code	Course Type	Regular Semester	Theory	Practice	Lab	Credits	ECTS
BUS 202	B	4	4	0	0	4	5

Academic staff member responsible for the design of the course syllabus (name, surname, academic title/scientific degree, email address and signature)	NA
Lecturer (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	Erjon Gjoçi , Tuesdays 9am-10am or by appointment
Second Lecturer(s) (name, surname, academic title/scientific degree, email address and signature) and Office Hours:
Teaching Assistant(s) and Office Hours:	Halisa Babasi
Language:	English
Compulsory/Elective:	Compulsory
Classroom and Meeting Time:	Online
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	Introduction & Syllabus
2	One-sample Hypothesis Testing (Chapter 10)
3	One-sample Hypothesis Testing (Chapter 10)
4	Two-sample Hypothesis Testing (Chapter 11)
5	Two-sample Hypothesis Testing (Chapter 11)
6	Analysis of Variance (Chapter 12)
7	Mid-term
8	Review
9	Correlation and Linear Regression (Chapter 13)
10	Correlation and Linear Regression (Chapter 13)
11	Multiple Regression Analysis (Chapter 14)
12	Multiple Regression Analysis (Chapter 14)
13	Presentations
14	Course Review

Prerequisite(s):	BUS 201: Statistics I
Textbook:	Statistical Techniques in Business & Economics, 15e: Lind, Marchal, Wathen.
Other References:
Laboratory Work:
Computer Usage:	YES
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.
Bachelor in Business Informatics (3 years) Program

COURSE EVALUATION METHOD

Method	Quantity	Percentage
Midterm Exam(s)	1	25
Presentation	1	20
Project	1	20
Final Exam	1	25
Attendance		10
	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	10	10
Assignments	1	10	10
Final examination	1	10	10
Other	1	15	15
Total Work Load:			125
Total Work Load/25(h):			5
ECTS Credit of the Course:			5