EPOKA UNIVERSITY
FACULTY OF ECONOMICS AND ADMINISTRATIVE SCIENCES
DEPARTMENT OF BUSINESS ADMINISTRATION
COURSE SYLLABUS
2023-2024 ACADEMIC YEAR
COURSE INFORMATIONCourse 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. Arjona Lami acela@epoka.edu.al , Friday 9:00-11:00 |
| 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 Economics (3 years) |
| Classroom and Meeting Time: | Tuesday 11:40-13:30, Thursday 10:40-12:30 |
| 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 ∕ √ 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 | 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 | Midterm Exam |
| 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): | Elementary Statistics by Allan G. Bluman, 11th ed. (2022), McGraw Hill |
| Additional Literature: | NA |
| Laboratory Work: | Yes |
| Computer Usage: | Yes |
| 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 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 | 4 | 64 |
| Hours for off-the-classroom study (Pre-study, practice) | 16 | 2 | 32 |
| Mid-terms | 1 | 12 | 12 |
| Assignments | 0 | ||
| Final examination | 1 | 17 | 17 |
| Other | 0 | ||
|
Total Work Load:
|
125 | ||
|
Total Work Load/25(h):
|
5 | ||
|
ECTS Credit of the Course:
|
5 | ||
|
CONCLUDING REMARKS BY THE COURSE LECTURER
|
|
As we reach the conclusion of this undergraduate course in statistics, it's important to reflect on the journey we've undertaken together. Throughout this course, we've explored the foundational principles and techniques that underpin the field of statistics, from descriptive statistics and probability theory to inferential methods. I believe students were able to learn basic concepts and theories. |