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
Main Course Lecturer (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	Dr. Fatbardha Morina fmorina@epoka.edu.al , 08:30-16:30
Second Course 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
Study program: (the study for which this course is offered)	Bachelor in International Marketing and Logistics Management (3 years)
Classroom and Meeting Time:	E-B32 Tuesday 10:45-11:30 11:45-12:30/ Wednesday 14:45-15:30 15:45-16:30
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 is specifically designed to provide knowledge related to intervals of confidence, hypothesis testing and regression analysis. At the end of the course, student should be able to understand the fundamentals of statistical inference.

BASIC CONCEPTS OF THE COURSE

1	confidence interval - a specific interval estimate of a parameter determined by using data obtained from a sample and the specific confidence level of the estimate
2	degrees of freedom - the number of values that are free to vary after a sample statistic has been computed; used when a distribution (such as the t distribution) consists of a family of curves
3	disordinal interaction- an interaction between variables in ANOVA, indicated when the graphs of the lines connecting the mean intersect
4	explanatory variable - a variable that is being manipulated by the researcher to see if it affects the outcome variable
5	independence test - a chi-square test used to test the independence of two variables when data are tabulated in table form in terms of frequencies
6	left-tailed test - a test used on a hypothesis when the critical region is on the left side of the distribution
7	parametric tests - statistical tests for population parameters such as means, variances, and proportions that involve assumptions about the populations from which the samples were selected
8	type I error - the error that occurs if you reject the null hypothesis when it is true
9	type II error - the error that occurs if you do not reject the null hypothesis when it is false
10	t distribution - a family of bell-shaped curves based on degrees of freedom, similar to the standard normal distribution with the exception that the variance is greater than 1; used when you are testing small samples and when the population standard deviation is unknown

COURSE OUTLINE

Week	Topics
1	Introduction to syllabus
2	Chapter 7: 7–1 Confidence Intervals for the Mean When σ Is Known. 7–2 Confidence Intervals for the Mean When σ Is Unknown (Page 369- 389)
3	Chapter 7: 7–3 Confidence Intervals and Sample Size for Proportions. 7–4 Confidence Intervals for Variances and Standard Deviations (Page 390- 412)
4	Chapter 8: 8–1 Steps in Hypothesis Testing—Traditional Method. 8–2 z Test for a Mean. 8–3 t Test for a Mean (Page 413-452).
5	Chapter 8: 8–4 z Test for a Proportion. 8–5 𝛘2 Test for a Variance or Standard Deviation. 8–6 Additional Topics Regarding Hypothesis Testing. (Page 453-513)
6	Chapter 9: 9–1 Testing the Difference Between Two Means: Using the z Test. 9–2 Testing the Difference Between Two Means of Independent Samples: Using the t Test (Page 514-533)
7	Chapter 9: 9–4 Testing the Difference Between Proportions. 9–5 Testing the Difference Between Two Variances (Page 534 - 573)
8	Review and Exercises
9	Midterm exam
10	Chapter 10: 10–1 Scatter Plots and Correlation. 10–2 Regression (Page 573-580)
11	Chapter 10: 10–3 Coefficient of Determination and Standard Error of the Estimate 10–4 Multiple Regression (Page 580-606)
12	Chapter 12: Analysis of Variance. 12–1 One-Way Analysis of Variance–2 The Scheffé Test and the Tukey Test. 12–3 Two-Way Analysis of Variance . (PAge 645- 685)
13	Chapter 13: Nonparametric Statistics 13–1 Advantages and Disadvantages of Nonparametric Methods13–2 The Sign Test 13–3 The Wilcoxon Rank Sum Test 13–4 The Wilcoxon Signed-Rank Test 13–6 The Spearman Rank Correlation Coefficient and the Runs Test (Page 685-755)
14	Review and Exercises

Prerequisite(s):	Statistics I
Textbook(s):	Allan G. Bluman (2017) Elementary Statistics , 10th ed., McGraw Hill
Additional Literature:	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	Confidence Intervals
2	Hypothesis testing
3	Regression 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.	5
2	Apply key theories to practical problems within the global business context.	5
3	Demonstrate ethical, social, and legal responsibilities in organizations.	5
4	Develop an open minded-attitude through continuous learning and team-work.	5
5	Use technology to enable business growth and sustainability.	5
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.	5
8	Integrate the management of logistics, supply chain and in total operations with corporate goals and strategies.	5

COURSE EVALUATION METHOD

Method	Quantity	Percentage
Midterm Exam(s)	1	30
Project	1	15
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)	2	20	40
Mid-terms	1	15	15
Assignments	1	7	7
Final examination	1	15	15
Other			0
Total Work Load:			125
Total Work Load/25(h):			5
ECTS Credit of the Course:			5

CONCLUDING REMARKS BY THE COURSE LECTURER

NA