COURSE INFORMATION Course Title: STATISTICS I

Code	Course Type	Regular Semester	Theory	Practice	Lab	Credits	ECTS
BUS 201	A	3	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:	Erindi Allaj , Monday - Thursday: 8.30 - 17.30
Second Lecturer(s) (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	NA
Teaching Assistant(s) and Office Hours:	NA
Language:	English
Compulsory/Elective:	Compulsory
Classroom and Meeting Time:
Course Description:	Statistics I: 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:	The main goals of this course are to help students to organize and analyze data to make sound business decisions, to provide the necessary statistical knowledge to be able to interpret statistical results in real-world business situations and research papers and to support further studies in business, economics and finance.

COURSE OUTLINE

Week	Topics
1	Course Introduction; The aim of Statistics; Data and Statistics
2	Summarizing Categorical and Quantitative Data
3	Descriptive Statistics: Numerical Measures; Measures of Location
4	Descriptive Statistics: Measures of Variability
5	Introduction to Probability; Basic Relationships of Probability
6	Conditional Probability; Bayes' Theorem
7	Introduction to Random Variables; Midterm Review
8	Midterm Exam
9	Discrete Random Variables
10	Continuous Random Variables
11	Sampling and Sampling Distributions; Point Estimation
12	Introduction to Sampling Distributions; Properties of Point Estimators
13	Interval Estimation
14	Course Review

Prerequisite(s):
Textbook:	Statistics for Business & Economics, 13th Edition, David R. Anderson; Dennis J, Sweeney; Thomas A, Williams; Jeffrey D. Camm; James J. Cochran, 2017
Other References:	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
Laboratory Work:
Computer Usage:
Others:	No

COURSE LEARNING OUTCOMES

1	Organize and present statistical data
2	Interpret and analyze statistical data using frequency distributions
3	Using measures of location and variability to describe central tendency and dispersion in a data set
4	Using probability in business decision making
5	Understand statistical inference; point estimation and interval estimation
6	To apply probability distributions for making business decisions

COURSE CONTRIBUTION TO... PROGRAM COMPETENCIES (Blank : no contribution, 1: least contribution ... 5: highest contribution)

No	Program Competencies	Cont.
Bachelor in International Marketing and Logistics Management (3 years) Program
1	Identify activities, tasks, and skills in management, marketing, accounting, finance, and economics.	1
2	Apply key theories to practical problems within the global business context.	1
3	Demonstrate ethical, social, and legal responsibilities in organizations.	1
4	Develop an open minded-attitude through continuous learning and team-work.	1
5	Use technology to enable business growth and sustainability.	1
6	Synthesize creativity needed for marketing notion with scientific method and numerical skills, for achieving business sustainability.	1
7	Apply the concepts and structures of modern marketing in global context at private and public sectors.	1
8	Integrate the management of logistics, supply chain and in total operations with corporate goals and strategies.	1

COURSE EVALUATION METHOD

Method	Quantity	Percentage
Midterm Exam(s)	1	35
Quiz	2	5
Final Exam	1	45
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)	15	2	30
Mid-terms	1	15	15
Assignments			0
Final examination	1	20	20
Other	2	6	12
Total Work Load:			125
Total Work Load/25(h):			5
ECTS Credit of the Course:			5