20. Syllabus Statistics for business and economics - Course Title: STATISTICS FOR BUSINESS AND - Studocu

Course Title: STATISTICS FOR BUSINESS AND ECONOMICS

2. Course Code: STA

3. Program: Business Administration

Credit Number: 3
Course Aims:

The course provides knowledge and cultivates skills on statistical methods for
collecting, organizing, presenting, analyzing and interpreting data on phenomena in

business and economics, thereby supporting to make decisions. Subjects of the course
include: introducing applications and terms of statistics, descriptive statistics, random

variables and probability distribution, sampling and estimating parameters from sample
data, testing hypotheses, analyzing the relationship between variables, analyzing time
data, methods calculating index, forecasting the future of phenomena, analysis of

variance on the experimental design models.

Course Learning Outcomes (CLO)

CLO
code Course Learning Outcomes
1 CLO1 Interpret rightly the use of the descriptive statistics tools
2 CLO2 Interpret rightly the core contents of inferential statistics
3 CLO3 Perform rightly the basic statistical methods by hand
4 CLO4 Analyze rightly a practical case study using statistical methods

5 CLO

Practice rightly the statistical methods in the course content by
SPSS software

6 CLO

Present clearly and convincingly by written documents plus word of
mouth, and slideshow facilities on a part of resulting of a team
research project
7 CLO7 Positive and honest in the application of statistics tools
Matrix showing the alignment of Course Learning Outcomes (CLO) with Program
Learning Outcomes (PLO)

Course Learning
Outcomes/ Program
Learning Outcomes

PLO1PLO2PLO3PLO4PLO5PLO6PLO7PLO8PLO9PLO10PLO11PLO

CLO1 X

CLO2 X

CLO3 X

CLO4 X

CLO5 X

CLO6 X

CLO7 X

Overall X X X X X

Students Responsibilities

Actively participate in the learning process and apply learned contents into practice.
Read relevant chapters of textbooks, materials and information on designated sites

before class.

Discuss and debate on topics and issues related to course content.
Do applied exercises in class and at home.
Implement a team research project; present the research results to the class.

Course Materials

8 Course book

TEXT 1. The lecture by lecturer
TEXT 2. Statistics for Business and Economics; Anderson, Sweeney, Williams,
Camm, Cochran; Cengage Learning (2012)

8 Reference book(s)

MTR 1. Nguyên lý thống kê kinh tế, Hà Văn Sơn, Nxb Kinh tế TP. Hồ Chí Minh
(2010)
MTR 2. Thống kê ứng dụng trong quản trị kinh doanh và nghiên cứu kinh tế, Trần
Bá Nhẫn-Đinh Thái Hoàng, Nxb Trường Đại học kinh tế Tp HCM (2003)
MTR 3. Phân tích dữ liệu nghiên cứu với SPSS; Hoàng Trọng-Chu Nguyễn Mộng

Ngọc; Nxb Hồng Đức (2008)

Grading Policy: Credit Based System
Detailed Course Content

CHAPTER 1 INTRODUCTION TO STATISTICS

measures
2.4 Measures of center location (measures of central tendency)
2.4 Measures of dispersion (measures of variability)
2.4 Quartiles and box plot
2 Measures of distribution shape
2 Measures of association between two quantitative variables
2.6 Covariance
2.6 Correlation coefficient (Pearson correlation coefficient)
2.6 Rank correlation coefficient (Spearman correlation coefficient)
2 Measures of association between two qualitative variables
2.7 Measures of association between two nominal variables
2.7 Measures of association between two ordinal variables

Reading materials
MTR1 Chapter 2 of TEXT
MTR2 Chapter 2 and Chapter 3 of TEXT 2
MTR3 Chapter 3 and Chapter 4 of MTR 3

CHAPTER 3 PROBABILITY DISTRIBUTION OF RANDOM VARIABLE

3 Random variables
3.1 Concept of random variable
3.1 Probability distribution of random variable
3 Basic parameters of random variable
3.2 Expected value
3.2 Variance
3.2 Covariance
3 Some basic probability distributions commonly used in statistics
3.3 Bernoulli probability distribution
3.3 Binomial probability distribution
3.3 Standard normal probability distribution
3.3 Normal probability distribution and the central limit theorem
3.3 Chi-squared probability distribution
3.3 Student probability distribution
3.3 Fisher-Snedecor probability distribution

Reading materials
MTR1 Chapter 3 of TEXT 1
MTR2 Chapter 4, Chapter 5, and Chapter 6 of TEXT 2

CHAPTER 4 SAMPLING AND ESTIMATION FOR A POPULATION

4 Selecting a Sample
4.1 Simple random sample, random sample
4.1 Sampling with replacement, sampling without replacement
4.1 Practice methods for selecting a sample
4 Parameters and statistics
4.2 Parameters of a population
4.2 Statistics of a sample
4 Sampling distribution
4.3 Sampling distribution of sample mean
4.3 Sampling distribution of sample proportion
4.3 Sampling distribution of sample variance
4 Point estimation
4.4 Properties of Point estimators
4.4 Point estimation for mean, proportion and variance
4 Interval estimation
4.5 Interval estimation for population mean
4.5 Interval estimation for population proportion
4.5 Interval estimation for population variance
4 Determining the sample size
The sample size for estimating population mean
The sample size for estimating population proportion

Reading materials
MTR1 Chapter 4 of TEXT 1
MTR2 Chapter 7 and Chapter 8 of MTR 2

CHAPTER 5 PARAMETER TEST AND DIFFERENCE ESTIMATION

samples (matched samples), Wilcoxon signed-Rank test
6.2 Testing hypotheses for comparison between two populations: paired
samples (matched samples), Sign test
6.2 Testing hypotheses for comparison between two populations:
independent samples, Mann-Whitney-Wilcoxon test
6.2 Testing hypotheses for comparison between many populations:
Kruskal-Wallis test
6 Testing hypotheses for relationship between variables
6.3 Testing hypotheses for correlation between two quantitative
variables: Spearman test
6.3 Testing hypotheses for relationship between two nominal variables:
Chi-Square test
6.3 Testing hypotheses for relationship between two ordinal variables:
Gamma test, Kendall-Tau test
6 Testing hypotheses for distribution of a population
6.4 Testing hypotheses for distribution of a population: Chi-square test
6.4 Testing hypotheses for normal distribution of a population:
Kolmogorov-Smirnov test

Reading materials
MTR1 Chapter 6 of TEXT 1
MTR2 Chapter 12 and Chapter 18 of TEXT 2
MTR3 Chapter 4 and Chapter 6 of MTR 3

CHAPTER 7 REGRESSION

7 Linear regression between two quantitative variables
7.1 Linear population regression model
7.1 Linear sample regression model
7.1 Determining coefficients of a sample regression function
7.1 Assumptions of linear regression model with two variables
7.1 Coefficient of determination
7.1 Testing for significance of population regression model: t Test, F Test
7 Non-linear regression between two quantitative variables
7.2 Exponential model

7.2 Power model
7.2 Logarithmic model
7.2 Inverse model
7.2 Quadratic model
7.2 Cubic model
7.2 Selecting a good regression model
7 Linear multiple regression between many quantitative variables
7.3 Linear multiple regression model
7.3 Determining coefficients of a sample regression function
7.3 Multiple coefficient of determination
7.3 The meaning of regression coefficients
7.3 Testing for significance of population regression model: t Test
7.3 Testing for significance of population regression model: F Test
7.3 Checking the assumptions of the model
7 Regression with qualitative data, time series data
7.4 Regression with categorical independent variables
7.4 Regression with time series data

Reading materials
MTR1 Chapter 7 of TEXT 1
MTR2 Chapter 14, Chapter 15 and Chapter 16 of TEXT 2
MTR3 Chapter 7 of MTR 3

CHAPTER 8 TIME SERIES ANALYSIS, FORECASTING AND INDEX

8 Time series
8.1 Concept and classification
8.1 Components of time series
8 Measures summarizing time series data
8.2 Mean
8.2 The amount of increase (decrease)
8.2 Change rate (index)
8.2 Growth rate
8 Describing basic trend of a phenomenon (smoothing time series)
8.3 Moving average method
8.3 Trend regression method

Matrix showing the alignment of Course Learning Outcomes (CLO) with Course Contents

Chapter
CLO1CLO2CLO3CLO4CLO5CLO6CLO

1 Introduction to statistics X
2 Descriptive statistics X X X X X
3 Probability distributions of random variables X
4 Sampling and estimation for a population X X X X X
5 Parameter test and difference estimation X X X X X
6 Non-parametric test X X X X X
7 Regression X X X X X
8 Time series analysis, forecasting and index X X
9 Analysis of variance X X X X X

Matrix showing the alignment of Course Learning Outcomes (CLO) with Teaching Learning Methods (TLM)

TLM
Code

Teaching Learning Methods

TLM

Group CLO1CLO2CLO3CLO4CLO5CLO6CLO

1 TLM1 Explicit Teaching 1
2 TLM2 Lecture 1
3 TLM3 Guest lecture 1
4 TLM4 Problem Solving 2
5 TLM5 Brainstorming 2
6 TLM6 Case Study 2
7 TLM7 Role play 2
8 TLM8 Game/ Oral Presentation 2
9 TLM9 Field Trip 2
10 TLM10 Debates 3 X X X X X X
11 TLM11 Discussion 3 X X X X
12 TLM12 Teamwork Learning 3 X
13 TLM13 Inquiry 4
14 TLM14 Research Project/ Independent Study 4 X
15 TLM15 Technology Based Methods 5
16 TLM16 Work Assignment 6 X X X X
17 TLM17 Others 7

Notes: Number of practice/discussion periods in reality is twice of the designed period number of practical work/discussion
– TLM

8 Time series analysis, forecasting and index
– TLM
– TLM
– TLM
9 Analysis of variance
– TLM
– TLM
– TLM
– TLM
– TLM
- Overall

Matrix showing the alignment of Course Learning Outcomes (CLO) with Assessment Methods (AM)

Code Assessment Methods

AM

Group CLO1CLO2CLO3CLO4CLO5CLO6CLO

1 AM1 Attendance Check 1 X
2 AM2 Work Assigment 1 X
3 AM3 Oral Presentation 1
4 AM4 Performance Test 2
5 AM5 Journal and Blogs 2
6 AM6 Essay 2 X X X X
7 AM7 Multiple Choice Exam 2
8 AM8 Oral Exam 2
9 AM9 Written Report 2 X X X X
10 AM10 Oral Presentation 3 X X X X
11 AM11 Teamwork Assessment 3
12 AM12 Graduation Thesis/ Report 3
13 AM13 Others 4