Course Syllabus

Course Information：

Year-Semester Course Number Course Name Phase Credits Hours Required/Elective Instructor Class Student NO. Withdraw Note

Fall Semester
Year 2025 348579 Statistics (I) 1 3.0 3 ▲ Ting, Hsiu-I 4IFM2 71 1 　

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Fall Semester Year 2025	348579	Statistics (I)	1	3.0	3	▲	Ting, Hsiu-I	4IFM2	71	1

Course Plan：

Instructor Ting, Hsiu-I　Office Hours

Email hiting@ntut.edu.tw

Last Updated 2025-05-27 18:08:25

Course Objective The purpose of this course is to familiarize students with frequently used statistical methods and theories. Students will be able to draw appropriate conclusions through problem identification, data collection, and appropriate statistical analysis methods. The course includes: descriptive statistics, probability concepts, probability distribution, interval estimation, hypothesis test, variance analysis, and regression analysis.

Course Schedule 1 Ch1 Data and Statistics. 2 Ch2 Descriptive Statistics: Tabular and Graphical Displays. 3 Ch2 4 Ch3 Descriptive Statistics: Numerical Measures. 5 Day off 6 Ch3 7 Descriptive Statistics Report Ch4 Introduction to Probability. 8 Day off 9 Ch4 10 Ch5 Discrete Probability Distributions. 11 Ch5 12 Ch6 Continuous Probability Distributions. 13 Mid-term exam 14 Ch7 Sampling and Sampling Distributions. 15 Ch7 16 Ch8 Interval Estimation. 17 Ch8 18 Final exam

Evaluation and grading policy Assignments & quiz 40% Report 20% Mid-term exam 20% Final exam 20%

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:Yes
Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann, David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Statistics for Business & Economics (15e).

The access to curricular consultation Please contact via email

Expanding teaching and resources

The course corresponds to the SDGs SDG1：消除貧窮（No Poverty）
SDG8：尊嚴就業與經濟發展（Decent Work and Economic Growth）
SDG10：減少不平等（Reduced Inequalities）

Does the course incorporate AI ● 使用生成式AI作為教學過程的輔助工具（Use generative AI tools as an aid to the teaching process）
● 鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools）

Note
If necessary, we will use Microsoft Teams for online teaching.

Instructor	Ting, Hsiu-I　Office Hours
Email	hiting@ntut.edu.tw
Last Updated	2025-05-27 18:08:25
Course Objective	The purpose of this course is to familiarize students with frequently used statistical methods and theories. Students will be able to draw appropriate conclusions through problem identification, data collection, and appropriate statistical analysis methods. The course includes: descriptive statistics, probability concepts, probability distribution, interval estimation, hypothesis test, variance analysis, and regression analysis.
Course Schedule	1 Ch1 Data and Statistics. 2 Ch2 Descriptive Statistics: Tabular and Graphical Displays. 3 Ch2 4 Ch3 Descriptive Statistics: Numerical Measures. 5 Day off 6 Ch3 7 Descriptive Statistics Report Ch4 Introduction to Probability. 8 Day off 9 Ch4 10 Ch5 Discrete Probability Distributions. 11 Ch5 12 Ch6 Continuous Probability Distributions. 13 Mid-term exam 14 Ch7 Sampling and Sampling Distributions. 15 Ch7 16 Ch8 Interval Estimation. 17 Ch8 18 Final exam
Evaluation and grading policy	Assignments & quiz 40% Report 20% Mid-term exam 20% Final exam 20%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann, David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Statistics for Business & Economics (15e).
The access to curricular consultation	Please contact via email
Expanding teaching and resources
The course corresponds to the SDGs	SDG1：消除貧窮（No Poverty） SDG8：尊嚴就業與經濟發展（Decent Work and Economic Growth） SDG10：減少不平等（Reduced Inequalities）
Does the course incorporate AI	● 使用生成式AI作為教學過程的輔助工具（Use generative AI tools as an aid to the teaching process） ● 鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools）
Note	If necessary, we will use Microsoft Teams for online teaching.