國立中興大學教學大綱

課程名稱	(中) 統計學(二)(1981)
	(Eng.) Statistics (II)
開課單位	管理學院
課程類別	必修	學分	3	授課教師	何彥臻
選課單位	行銷系 / 學士班	授課使用語言	英文	英文/EMI	Y	開課學期	1122
課程簡述	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.
先修課程名稱						課程含自主學習	Y

課程與核心能力關聯配比(%)

課程目標之教學方法與評量方法

課程目標

核心能力

配比(%)

教學方法

評量方法

1. Basic statistical theorems
2. Data analysis using statistical techniques

1.獨立分析

2.專業知識

專題探討/製作

習作

實習

書面報告

作業

出席狀況

口頭報告

授課內容(單元名稱與內容、習作/每週授課、考試進度-共18週)

週次	授課內容
第1週	2/21 Ch10 Estimation and Hypothesis Testing for Two Population Parameters
第2週	2/28 National Holiday
第3週	3/6 Ch11 Hypothesis Tests and Estimation for Population Variances
第4週	3/13 Ch12 Analysis of Variance
第5週	3/20 Review 1
第6週	3/27 Test 1 (ch10, ch11, ch12)
第7週	4/3 Ch14 Introduction to Linear Regression and Correlation Analysis
第8週	4/10 Ch15 Multiple Regression and Model Building
第9週	4/17 Ch15 Multiple Regression and Model Building
第10週	4/24 Review 2
第11週	5/1 Test 2 (ch14, ch15)
第12週	5/8 Ch13 Goodness-of-fit Tests and Contingency Analysis
第13週	5/15 Ch16 Analyzing and Forecasting Time-Series Data
第14週	5/22 Ch17 Introduction to Nonparametric Statistics
第15週	5/29 Presentation rehearsal
第16週	6/5 Final presentation
第17週	Group projects [Self Learning]
第18週	Personal essays [Self Learning]

學習評量方式

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

教科書＆參考書目(書名、作者、書局、代理商、說明)

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.

課程教材（教師個人網址請列在本校內之網址）

see iLearning

課程輔導時間

Office hours by email appointment.
Teaching assistant sessions will be arranged online by appointment.

聯合國全球永續發展目標

04.教育品質 11.永續城市 17.全球夥伴

提供體驗課程：N

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更新日期西元年/月/日：2024/02/23 23:39:19	列印日期西元年/月/日：2024 / 4 / 27
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