1. COURSE DESCRIPTION
This course introduces the basic concepts and techniques of statistics, which is the study of how to collect, organize, summarize, present, and draw conclusions from data. Statistics is essential for many fields and applications that involve data analysis and interpretation. In this course, you will learn the fundamental principles and methods of statistics, such as descriptive statistics, estimation, hypothesis testing, and regression.
2. REASON FOR THE COURSE
This course can provide valuable skills and knowledge for students who are majoring in accounting and finance. Statistics can help them analyze data, interpret results, and make decisions based on empirical evidence. Statistics can also help them understand the concepts and methods of and assist them in carrying out their tasks of auditing, financial reporting, and risk management. A statistics course can enhance their critical thinking, problemsolving, and communication abilities, which are essential for their future careers. Therefore, taking a statistics course is a worthwhile investment for accounting and finance majors.
3. STUDY HOURS
4. ROLE IN CURRICULUM
Prerequisites:
There is no prerequisite for Introduction to Data Analysis in Business (STAT 111). However, to take this course students must have a strong foundation in algebra and be able to use a spreadsheet program, particularly Excel and Google Sheets.
On successful completion of this course, students will be able to:
Knowledge  Level of Learning 
Related PLO 

Describe statistical methods (CK1) Describe the methods for organizing, summarizing, interpreting, and drawing conclusions from businessrelated data 
Understand  PCIT1 
Cognitive Skills  Level of Learning 
Related PLO 
Apply statistical methods (CC1) Apply statistical methods to solve realworld business problems. 
Apply  PCIT1 
Write statistical analysis reports (CC2) Write reports of the statistical analysis results. 
Create  PCIT1 
Communication, Information Technology, and Numerical Skills  Level of Learning 
Related PLO 
Explain statistical results (CCIT1) Explain statistical results to both technical and nontechnical audiences. 
Apply  PCIT2 
Use spreadsheet software (CCIT2) Use spreadsheets such as Microsoft Excel/Google Sheets to analyze data. 
Apply  PCIT2 
Interpersonal Skills and Responsibilities  Level of Learning 
Related PLO 
Use statistics ethically (CIP1) Use statistics in an ethical and responsible way, in order to avoid misleading data and interpretation. 
Apply 
PCIT2 
Grades will be determined based on a grading score, calculated using the following assessments and score allocations:
SKILL  Assessment  Skill Weighting for Grade  

Participation  Quiz  Project  final case study  
Describe statistical methods (CK1)  60%  40%  10%  
Apply statistical methods (CC1)  60%  40%  20%  
Write statistical analysis reports (CC2)  60%  40%  30%  
Explain statistical results (CCIT1)  100%  10%  
Use spreadsheet software (CCIT2)  70%  30%  20%  
Use statistics ethically (CIP1)  100%  10% 
This course utilizes a variety of teaching methods, including lectures, demonstrations, questioning, and problemsolving discussions. Additionally, gamification tools such as Quiz or Kahoot are integrated into the class. Students will be assigned readings, homework, projects, and quizzes.
During the course, there is one project assignment:
Assignment:  Data Analysis for Business Research Project 
Work Group:  Group of 35 students 
Output Format  APA Format Report 
Language:  English 
Description:  Each team selects a relevant topic related to service, product, pricing, or a similar aspect. They create a survey to collect data, then use statistical data analysis skills to interpret, summarize, and draw conclusions. Finally, they present their findings in an APAformatted report. 
The course targets the 30 lessons in the study plan below. Each lesson is 1.5 class hours; there are a total of 45 class hours. The study plan below describes the skills to be learned in each lesson. Readings should be completed before the start of each class. Implementation of this study plan may vary depending on the progress and needs of students. References are supporting documents that students may optionally read for deeper understanding or clarification.
No  Lesson Learning Outcomes  Teaching (T), and Assessment (A) Methods 

1  Introduction to the course and overview of the course and requirements.  Lecture (T) Discussion (A) 
2 
Fundamental statistical terms

Lecture (T) Demonstration (T) Discussion (T, A) Quizizz/Kahoot (T, A) Reading: (Bluman, 2023, pp.211) 
3 
Sampling Techniques

Lecture (T) Demonstration (T) Questioning (T, A) Reading: (Bluman, 2023, pp.1117) 
4 
Organizing Data

Lecture (T) Demonstration (T) Questioning (T, A) Reading: (Bluman, 2023, pp.4253) 
5 
Organizing and presenting data

Lecture (T) Demonstration (T) Questioning (T, A) Quizizz/Kahoot (T, A) Reading: (Bluman, 2023, pp.59, 7686) 
6 
Measures of Central Tendency

Lecture (T) Demonstration (T) Questioning (T, A)Reading: (Bluman, 2023, pp.113123) 
7 
Measures of Variation

Lecture (T) Demonstration (T) Questioning (T, A)Reading: (Bluman, 2023, pp.131140) 
8 
Measures of Position

Lecture (T) Demonstration (T) Questioning (T, A)Reading: (Bluman, 2023, pp.131140) 
9 
A review of descriptive statistics

Discussion (T, A) Quizizz Game/Kahoot (T, A) 
10 
Quiz 1

Quiz (A) 
11 
Estimate the mean

Lecture (T) Demonstration (T) Questioning (T, A)Reading: (Bluman, 2023, pp. 370382) 
12 
Estimate the mean

Lecture (T) Demonstration (T) Questioning (T, A)Reading: (Bluman, 2023, pp. 383389) 
13 
Estimate the proportion

Lecture (T) Demonstration (T) Questioning (T, A)Reading: (Bluman, 2023, pp. 389397) 
14 
Estimate the variance and standard deviation

Lecture (T) Demonstration (T) Group problemsolving (T, A) Quizizz/Kahoot (T, A)Reading: (Bluman, 2023, pp. 404412) 
15 
A review of parameter estimation

Presenting(T) Group problemsolving (T, A)Quizizz/Kahoot (T, A) 
16 
Statistical hypothesis test

Lecture (T) Demonstration (T) Questioning (T, A) Quizizz/Kahoot (T, A) Reading: (Bluman, 2023, pp. 414427) 
17 
One Sample Z test for the mean

Lecture (T) Demonstration (T) Questioning (T, A) Group problemsolving (T, A)Reading: (Bluman, 2023, pp. 428441) 
18 
The difference between two means

Lecture (T) Demonstration (T) Questioning (T, A) Group problemsolving (T, A)Reading: (Bluman, 2023, pp. 490501) 
19 
One Sample ttest and independent sample ttest

Lecture (T) Demonstration (T) Questioning (T, A) Group problemsolving (T, A)Reading: (Bluman, 2023, pp. 503505, 507510) 
20 
Independent sample ttest and paired sample ttest

Lecture (T) Demonstration (T) Questioning (T, A) Group problemsolving (T, A)Reading: (Bluman, 2023, pp.509, 511522) 
21 
Z test for the proportion(s)

Lecture (T) Demonstration (T) Questioning (T, A) Group problemsolving (T, A)Reading: (Bluman, 2023, pp. 453461, 523531) 
22 
Difference between two variances

Lecture (T) Demonstration (T) Questioning (T, A) Group problemsolving (T, A)Reading: (Bluman, 2023, pp. 462474, 523531) 
23 
NonParametric Test

Lecture (T) Demonstration (T) Questioning (T, A) Group problemsolving (T, A)Reading: (Bluman, 2023, pp.613645) 
24 
A review of hypothesis test

Presenting(T) Group problemsolving (T, A) Quizizz/Kahoot (T, A) 
25 
Scatter Plot and Correlation Analysis

Lecture (T) Demonstration (T) Questioning (T, A) Group problemsolving (T, A)Reading: (Bluman, 2023, pp.551567) 
26 
Least Square Method

Lecture (T) Demonstration (T) Questioning (T, A) Group problemsolving (T, A)Reading: (Bluman, 2023, pp.551567) 
27 
Confidence Interval and Prediction Interval

Lecture (T) Demonstration (T) Questioning (T, A) Group problemsolving (T, A)Reading: (Bluman, 2023, pp.551567) 
28 
A Review of correlation and simple linear regression

Presenting(T) Group problemsolving (T, A) Quizizz/Kahoot (T, A) 
29 
Quiz 2

Quiz (A) 
30  Overall review for final exam  Presenting(T) Group problemsolving (T, A) Quizizz/Kahoot (T, A) 
Textbooks
Bluman, A. G. (2023). Elementary Statistics: A Step by Step Approach. New York: McGraw Hill Education
References
Lind, D. A., Marchal, W. G., and Wathen, M. (2021). Statistical Techniques in Business and Economics. New York: New York: McGraw Hill Education