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
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
Teaching Assistant(s) and Office Hours:	NA
Language:	English
Compulsory/Elective:	Compulsory
Study program: (the study for which this course is offered)	Bachelor in Banking and Finance (3 years)
Classroom and Meeting Time:	Monday 12:40-14:30 E-211 & Tuesday 11:40-13:30 E/B32
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 𝜎∕ √ n

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	Mid-term
8	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
9	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
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 and exam review

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 learn about the importance of statistics in practical life
2	Students will be able to calculate the average, variance and standard deviation
3	Students will be able to analyse and interpret the data using micro level data
4	Students will be able to use the concept of normal distribution and its importance in the statistical analysis

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

No	Program Competencies	Cont.
Bachelor in Banking and Finance (3 years) Program
1	The students gain the ability to look at the problems of daily life from a broader perspective with an increased awareness of the importance of moral/ethical considerations and professional integrity in the workplace.	4
2	They develop their knowledge and understanding of banking and finance including concepts, theories, and analytical tools that serve both in national and international markets.	2
3	They gain an understanding of the role of financial management in business firms and the essentials of corporate finance and further develop their knowledge in the field.	1
4	They are able to apply valuation models to estimate the price of different financial assets, measure risk and describe the risk-return tradeoff.	3
5	They are provided with the knowledge and understanding of the regulatory framework and functioning of banking system and central banking as well as international banking system.	1
6	They are able to understand and use fundamental economic theories and tools to solve economic problems in banking and financial services industry.	4
7	They have the ability to develop and utilize accounting, financial and economic data as well as other information to solve different business problems by making use of basic mathematical and statistical models.	5
8	They are expected to develop their numerical and IT skills as well as knowledge of databases in order to address the significant development in the delivery and use of financial services known as FinTech.	5
9	They develop their ability to think critically, do research, analyze, interpret, draw independent conclusions, and communicate effectively, both individually and as part of a team.	5
10	They are provided with opportunities to acquire the necessary skills and competencies to develop professionalism in the banking and financial services industry or to move on to further study within the discipline.	2

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