NCHU Course Outline
Course Name (中) 統計學(二)(1981)
(Eng.) Statistics (II)
Offering Dept College of Management
Course Type Required Credits 3 Teacher Yen-Chen Ho
Department Department of Marketing/Undergraduate Language English Semester 2025-SPRING
Course Description This year-round course equips undergraduate students with the foundational tools of statistics to navigate the complex world of business. Over the 2nd semester, we will delve into statistical analysis and practical applications, transforming data into actionable insights that inform effective decision-making.

The first part of the lecture begins with Estimation and Hypothesis Testing for population parameters, such as means and proportions, and subsequently tests hypotheses about them using confidence intervals and p-values. This initial exploration lays the groundwork for understanding the variability within and between populations, which we will delve into further by examining Population Variances. Analysis of Variance (ANOVA), a powerful statistical tool, will then be introduced, enabling us to compare multiple groups and draw meaningful conclusions. This technique is particularly valuable in scenarios where we wish to identify significant differences between multiple populations.

Next, we will introduce the basics of correlation and linear regression analysis, the statistical relationships between variables, and assess their effect sizes. Students will learn to identify patterns and estimate the models. Multiple Regression and Model Building will expand the introduction by incorporating multiple independent variables into our models. We will learn to evaluate model fit, diagnose potential issues, and refine our models for optimal performance.

Moving forward, we will proceed to intermediate-level contents, including Goodness-of-Fit Tests and Contingency Analysis, to assess how well data conforms to specific distributions and analyze relationships between categorical variables. Time-series analysis is a branch of statistical analysis that leverages historical data to forecast future trends and make informed predictions. The course will conclude with an introduction to Nonparametric Statistics, a branch of modern statistical techniques to analyze data without distributional assumptions.
Prerequisites
self-directed learning in the course Y
Relevance of Course Objectives and Core Learning Outcomes(%) Teaching and Assessment Methods for Course Objectives
Course Objectives Competency Indicators Ratio(%) Teaching Methods Assessment Methods
1. Basic statistical theorems
2. Data analysis using statistical techniques
1.Indenpendent Analysis
2.Professional Knowledge
40
60
topic Discussion/Production
Exercises
Practicum
Written Presentation
Assignment
Attendance
Oral Presentation
Course Content and Homework/Schedule/Tests Schedule
Week Course Content
Week 1 2/21 Ch10 Estimation and Hypothesis Testing for Two Population Parameters
Week 2 2/28 National Holiday
Week 3 3/6 Ch11 Hypothesis Tests and Estimation for Population Variances
Week 4 3/13 Ch12 Analysis of Variance
Week 5 3/20 Review 1
Week 6 3/27 Test 1 (ch10, ch11, ch12)
Week 7 4/3 Ch14 Introduction to Linear Regression and Correlation Analysis
Week 8 4/10 Ch15 Multiple Regression and Model Building
Week 9 4/17 Ch15 Multiple Regression and Model Building
Week 10 4/24 Review 2
Week 11 5/1 Test 2 (ch14, ch15)
Week 12 5/8 Ch13 Goodness-of-fit Tests and Contingency Analysis
Week 13 5/15 Ch16 Analyzing and Forecasting Time-Series Data
Week 14 5/22 Ch17 Introduction to Nonparametric Statistics
Week 15 5/29 Presentation rehearsal
Week 16 6/5 Final presentation
Week 17 Group projects [Self Learning]
Week 18 Personal essays [Self Learning]
Evaluation
Requirement Rating Evaluation
Attendance 10% Final personal essay (end-of-term) / Online quiz
Exams 60% 2 Tests - 30% each)
Final report 30% Final group report
Textbook & other References
Main textbook
Groebner, D. F., Shannon, P. W. & Fry, P. C. (2018) Business Statistics: A Decision-Making Approach (10th Edition), Pearson Education Inc.
Other reference
Levine, D. M., Stephan, D. F. & Szabat, K. A.(2017) Statistics for Managers: Using Microsoft Excel (8th Edition), Pearson Education Inc.
Teaching Aids & Teacher's Website
see iLearning
Office Hours
Office hours by email appointment.
Teaching assistant sessions will be arranged online by appointment.
Sustainable Development Goals, SDGs
04.Quality Education   11.Sustainable Cities and Communities   17.Partnerships for the Goalsinclude experience courses：N
Please respect the intellectual property rights and use the materials legally.Please repsect gender equality.
Update Date, year/month/day：None Printed Date, year/month/day：2025 / 1 / 22
The second-hand book website：http://www.myub.com.tw/