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)	Dr. Fatbardha Morina fmorina@epoka.edu.al
Main Course Lecturer (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	Dr. Fatbardha Morina fmorina@epoka.edu.al , Mondays: 14:00 - 16:00
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 Economics (3 years)
Classroom and Meeting Time:	Monday 08:45-10:30 E-311 & Tuesday 12:40-14:30 E-B32
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 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 major objective of this course is to increase the student data analysis skills using different statistical tools, both from descriptive and inferential statistics.

BASIC CONCEPTS OF THE COURSE

1	Variable - A variable is a characteristic or attribute that can assume different values.
2	Population - A population consists of all subjects (human or otherwise) that are being studied.
3	Inferential statistics - Inferential statistics consists of generalizing from samples to populations, performing estimations and hypothesis tests, determining relationships among variables, and making predictions.
4	Frequency distribution - A frequency distribution is the organization of raw data in table form, using classes and frequencies.
5	Parameter - A parameter is a characteristic or measure obtained by using all the data values from a specific population.
6	Probability experiment - A probability experiment is a chance process that leads to well-defined results called outcomes. An outcome is the result of a single trial of a probability experiment.
7	Histogram - Histogram a graph that displays the data by using vertical bars of various heights to represent the frequencies of a distribution
8	Random variable - A random variable is a variable whose values are determined by chance.
9	Normal distribution- If a random variable has a probability distribution whose graph is continuous, bellshaped, and symmetric, it is called a normal distribution. The graph is called a normal distribution curve.
10	Central limit theorem- central limit theorem a theorem that states that as the sample size increases, the shape of the distribution of the sample means taken from the population with mean and standard deviation will approach a normal distribution; the distribution will have a mean and a standard deviation ∕ √

COURSE OUTLINE

Week	Topics
1	Introduction to syllabus
2	Chapter 1. The nature of probability and statistics. 1.1Descriptive and Inferential Statistics pg 1-5. 1.2 Variables and Types of Data pg 6-8 1.3Data Collection and Sampling Techniques pg 9-13 1.4 Observational and Experimental Studies pg.13-16
3	Chapter 2. Frequency distribution and graphs. 2.1 Organizing Data Pg.36-50
4	Chapter 2. Frequency distribution and graphs. 2.2 Histograms, Frequency Polygons, and Ogives Pg.51-68 2.3 Other Types of Graphs Pg.68-101
5	Chapter 3 . Data description. 3.3Measures of central tendency Pg. 104-123 3.4 Measures of Variation Pg.123-142
6	Chapter 3. Data description. 3.4 Measures position. Pg.142-162 3.5 Exploratory Data Analysis Pg.162-180
7	Chapter 4. Probability and counting rules 4.1 Sample Spaces and Probability Pg.182-199 4.2 The Addition Rules for Probability Pg.199-211
8	Chapter 4. Probability and counting rules 4.3 The Multiplication Rules and Conditional Probability Pg.211-224 4.4 Counting Rules Pg.224-237 4.5Probability and Counting Rules Pg.237-250
9	Mid-term Exam
10	Chapter 5. Discrete Probability Distributions. 5.1 Probability Distributions Pg. 252-259 5.2. Mean, Variance, Standard Deviation, and Expectation Pg.259-270
11	Chapter 5. Discrete Probability Distributions 5.3 Binomial distribution Pg. 270-283 5.4 Other types of probability distribution Pg.270-295
12	Chapter 6. The normal distribution 6.1 Normal distribution Pg300-316 6.2 Applications of normal distribution Pg. 316-330
13	Chapter 6. The normal distribution 6.3 The Central Limit Theorem Pg. 331-340
14	Project presentation related to sustainability and circular economy.

Prerequisite(s):	NA
Textbook(s):	Allan G. Bluman (2017) Elementary Statistics , 10th ed., McGraw Hill
Additional Literature:	NA
Laboratory Work:	Yes
Computer Usage:	Excel
Others:	No

COURSE LEARNING OUTCOMES

1	Students will be able to use statistical terms like population, sample, and variable.
2	Students will be able to calculate and interpret mean, median, mode, and standard deviation.
3	Students will be able to create and analyze graphs like histograms and scatter plots.
4	Students will be able to apply basic probability rules and understand events.
5	Students will be able to identify and use different sampling techniques.
6	Students will be able to construct confidence intervals and conduct hypothesis tests.
7	Students will be able to analyze relationships between variables using correlation and simple regression.
8	Students will be able to use statistics to analyze data related to circular economy practices.

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

No	Program Competencies	Cont.
Bachelor in Economics (3 years) Program
1	Students define the fundamental problems of economics	2
2	Students describe key economic theories	2
3	Students critically discuss current developments in economics	2
4	Students appropriately use software for data analysis	5
5	Students critically contextualize the selection of an economic problem for research within scholarly literature and theory on the topic	4
6	Students apply appropriate analytical methods to address economic problems	5
7	Students use effective communication skills in a variety of academic and professional contexts	4
8	Students effectively contribute to group work	2
9	Students conduct independent research under academic supervision	5
10	Students uphold ethical values in data collection, interpretation, and dissemination	5
11	Students critically engage with interdisciplinary innovations in social sciences	2
12	Student explain how their research has a broader social benefit	5

COURSE EVALUATION METHOD

Method	Quantity	Percentage
Midterm Exam(s)	1	35
Project	1	15
Final Exam	1	40
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

Students are expected to have gained a comprehensive understanding of statistics. Meanwhile, students should work with real data from companies that operate in Albania in order to organize and interpret the data