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)	Dr. Arjona Lami acela@epoka.edu.al
Main Course Lecturer (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	M.Sc. Anisa Isufi aisufi@epoka.edu.al , E306, Thursday 11:00-12:00
Second Course Lecturer(s) (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	NA
Language:	English
Compulsory/Elective:	Compulsory
Study program: (the study for which this course is offered)	Bachelor in International Marketing and Logistics Management (3 years)
Classroom and Meeting Time:
Teaching Assistant(s) and Office Hours:	NA
Code of Ethics:	Code of Ethics of EPOKA University Regulation of EPOKA University "On Student Discipline"
Attendance Requirement:	75%
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:	This course aims to boost students' data analysis skills by exploring diverse statistical methodologies, including descriptive and inferential techniques. Objectives include mastering foundational statistical concepts, proficiency in data preprocessing, selecting appropriate methods, interpreting results, and developing critical thinking skills for effective analysis and communication. Through these objectives, students will be well-equipped to confidently navigate data-driven environments.

BASIC CONCEPTS OF THE COURSE

1	Confidence Interval
2	Hypotheses Testing
3	Analysis of Variance (ANOVA)
4	Nonparametric Statistics
5	Regression Analysis
6	Inferential Statistics
7	Descriptive Statistics
8	Population and Sample

COURSE OUTLINE

Week	Topics
1	Introduction to syllabus
2	In Chapter 6, titled "Distributions of Sample Statistics" on page 244, the discussion centers on the necessity of acquiring a representative sample from a population of interest with measured attributes for statistical analysis.
3	In Chapter 6, titled "Distributions of Sample Statistics" on page 244, the discussion centers on the necessity of acquiring a representative sample from a population of interest with measured attributes for statistical analysis.
4	In Chapter 6, titled "Distributions of Sample Statistics" on page 244, the discussion centers on the necessity of acquiring a representative sample from a population of interest with measured attributes for statistical analysis.
5	Chapter 7 Confidence Interval Estimation: One Population 284: In this chapter we address these and other types of situations that require an estimate of some population parameter.
6	Chapter 7 Confidence Interval Estimation: One Population 284: In this chapter we address these and other types of situations that require an estimate of some population parameter.
7	Revie for Midterm Exam
8	Midterm Exam
9	Chapter 9-10 Hypothesis Tests of a Single Population 346: In this chapter we develop hypothesis-testing procedures that enable us to test the validity of some conjecture or claim by using sample data
10	Chapter 11-13 Regression Models page 417-600: In this chapter we extend our analysis to relationships between variables.
11	Chapter 11-13 Regression Models page 417-600: In this chapter we extend our analysis to relationships between variables.
12	Chapter 15 Analysis of Variance 645: In modern business applications of statistical analysis, there are a number of situations that require comparisons of processes at more than two levels.
13	Project presentation.
14	Project presentation.

Prerequisite(s):	Statistics 1
Textbook(s):	Hogg, Tanis, and Zimmerman "Probability and Statistical Inference." 10th edition. Paul Newbold, William L. Carlson, and Betty Thorne “Statistics for Business and Economics” latest edition Anderson, Sweeney, Williams "STATISTICS FOR BUSINESS AND ECONOMICS"
Additional Literature:	Casella and Berger's Statistical Inference
Laboratory Work:	Yes
Computer Usage:	Yes
Others:	No

COURSE LEARNING OUTCOMES

1	Gain a comprehensive understanding of the importance of acquiring a representative sample from a population for statistical analysis, recognizing that the integrity and accuracy of statistical methods hinge upon the adequacy of the sample, thereby ensuring valid inferential conclusions.
2	Apply confidence interval estimation methods to estimate population parameters, demonstrating the ability to make inferential statements based on information derived from random samples, thereby enhancing the capacity for statistical inference in real-world situations.
3	Analyze relationships between variables using regression models, extending beyond descriptive relationships through the interpretation of scatter plots and covariance/correlation coefficients, thereby fostering a deeper understanding of the interplay between variables in statistical analysis.

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.	3
2	Apply key theories to practical problems within the global business context.	3
3	Demonstrate ethical, social, and legal responsibilities in organizations.	4
4	Develop an open minded-attitude through continuous learning and team-work.	3
5	Use technology to enable business growth and sustainability.	3
6	Synthesize creativity needed for marketing notion with scientific method and numerical skills, for achieving business sustainability.	5
7	Apply the concepts and structures of modern marketing in global context at private and public sectors.	2
8	Integrate the management of logistics, supply chain and in total operations with corporate goals and strategies.	2

COURSE EVALUATION METHOD

Method	Quantity	Percentage
Midterm Exam(s)	1	30
Project	1	40
Final Exam	1	30
	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	4	64
Mid-terms			0
Assignments			0
Final examination	1	30	30
Other	1	8	8
Total Work Load:			150
Total Work Load/25(h):			6
ECTS Credit of the Course:			5

CONCLUDING REMARKS BY THE COURSE LECTURER

If a student receives a misbehavior report, they will automatically receive zero points for the exam. The same applies to projects with high plagiarism.