統計學 (二): 度教師自評: 甜度: ★★★✩✩ | 涼度: ★★✩✩✩
第一週上課,老師會說明個人教學理念、授課風格及本課程設計安排,若自覺得不合適不喜歡不想配合或這們課無法達到您的預期或有不得已的苦衷(請告知),請勿選修或請期中棄修,感謝~感恩!! 這裡有教師【歷年教學意見調查】及【政大課程評價網】供您選課參考,也可至【迪卡搜尋漢銘】。

  • 想輕鬆得高分者、對考題有名詞解釋及問答題不喜歡者、對教師英語教學的發音很要求者,不建議選修本課程。(For those who want to easily get high scores, who do not like exam questions that involve explaining terms and answering questions, who are very particular about the teacher's pronunciation in English teaching, it is recommended not to take this course.)

Subject:Statistics (II)  [112 (2): 2024/02~2024/06] (English)

Lecturer: Han-MIng Wu (Department of Statistics,  Associate Professor), Office: College of Commerce 261103,  ext: 81103。

Office Hour 一/13:00~15:00E-mail: wuhm@g.nccu.edu.tw

Course ID: 000359221。Required/Selective: required。Credit:3 。Time/Place:  Thu D56, 商館260306

TA Class:

  • Students who have a schedule conflict with the TA class cannot enroll. (School's policy)
  • Date/Time: Tue 78,Place: TBA。(once/week, or biweekly depend on TA)
  • Free to join TA class, no roll call.
  • TA: Master Student of Dep. of Statistics, Che-Wei Lin (林哲緯) (email, FB)(Office hours: TBA, at 9th floor, College of Commerce (每星期??在商院九樓討論區))。
  • TA's Teaching Material: the link will be announced in Class FB.。
  • TA's Duties: Answering students' course questions, preparing teaching materials for TA classes (including R programming) and explaining some exercises, and reporting students' learning issues to the teacher, proctoring exams, correcting the exam paper and grading.

 

Announcement

  • Top: [2024/02/04] Scoring Sheet。(updated: 2024/02/04)
  • [2024/02/15] 教發中心自113年2月2日(五)至2月25日(日)受理112學年度第2學期學生課業諮詢輔導申請。Doc1 | Doc2 | 申請網址:https://reurl.cc/g4DnjL
  • [2024/02/04] The class videos will be released after class for students to review. The link will be announced on the course's FB. (<前學期中文版影片也會提供學生學習參考>)
  • [2024/02/04] Lecture notes: [Teacher's Version] [Student's Version]。(Please do not ask the teacher for the solution to the lecture notes' computational/application questions and past exam questions.)
  • [2024/02/04] The dataset used in this textbook.
  • [2024/02/04] There are parts of solutions of selected exercises of each chapter posted on the Teaching Material Link of TA.
  • [2024/02/04] (加選注意事項) Students who wish to add this course, please print the "Course Add Form" and give it to the teacher for signature during the first class, or, email the PDF file of the "Course Add Form" to the teacher for signature. (No further additions will be allowed once the maximum number of students is reached.)
  • [2023/02/04] (!! Important !!) Please, students taking the course, join the private Facebook group for the course.:「112-2-統計學 (二)課程FB社團」。(Not mandatory)
    • Students can post questions in the course FB group (either anonymously or with their real name), and TA/teacher will answer later.
    • The TA/teacher will post real-time news, exam hints, class video URLs, or upload account and password information in the course FB group.
    • The TA/teacher will not accept course-related questions through Facebook private messages or emails..
    • If you have personal questions, you can send a private message or email to the TA or teacher.
  • [2024/02/04] 校訂教學計畫表。Please adhere to the following "Teaching Content and Schedule". Modifications will be made at any time based on the actual progress of the teaching.
  • [2024/02/04] 統計學整合開課】Course selection instructions: Please refer to the school's regulations.。

 

Course Description

This course primarily introduces the theory and computational methods of statistics, along with its application in business. The textbook used is "Anderson et al., 2019, Statistics for Business & Economics (14th Edition), Cengage Learning Ltd. (ISBN: 0357114485)." The topics for the next semester include hypothesis testing, inference on population variance, multiple proportion comparisons, independence tests, experimental design, analysis of variance, regression analysis, and non-parametric methods, among others. The teaching method in the classroom is primarily lecture-based. In addition to teaching the theory of statistics, data analysis and report interpretation for the above topics will also be conducted using R software. (Note: The weekly course progress and homework requirements will be adjusted according to the actual teaching situation.) (The course is taught in English)

Course Objectives & Learning Outcomes

The teaching objectives of this course are to enable students to possess the following abilities after completing it: (1) Understand and explain the specialized terminology used in various application areas of statistics. (2) Comprehend the main theories behind independence tests and goodness-of-fit tests. (3) Understand the principles of experimental design, analysis of variance, regression analysis, and non-parametric methods, and be able to apply them to real-world problems to make statistical inferences. (4) Conduct data analysis for the topics taught this semester using statistical software (R). (5) Interpret the reports and charts generated by statistical software (R).

 

(Course Schedule & Requirements) (Subject to modifications at any time based on the actual progress of the teaching.)

Week MM/DD Topic

Note

1 02/22 Course Introduction、Review  
2 02/29 
Ch9: Hypothesis Tests  
3 03/07 Ch10: Inference about Means and Proportions with Two Populations
4 03/14 Ch10: Inference about Means and Proportions with Two Populations
5 03/21
Ch11: Inference about Population Variances quiz (1):
6 03/28
Ch11: Inference about Population Variances
7 04/04 (Holiday) Ch12: Comparing Multiple Proportions,Test of Independence and Goodness of Fit  
8 04/11 Demonstration using R (I) (Online, MS Teams) [16+2教學規劃: Online Learning]
9 04/18

MIdterm exam

Midterm exam

10 04/25

Ch12: Test of Independence and Goodness of Fit

11 05/02

Ch13: Analysis of Variance. (SKIP)

Ch14: Simple Linear Regression.

 
12 05/09 (調課) Ch14: Simple Linear Regression.  
13 05/16 Ch15: Multiple Regression  
14 05/23 Ch16: Regression Analysis: Model Building (SKIP) quiz (2)
15 05/30
Ch17: Time Series Analysis and Forecasting  
16 06/06 Ch18: Nonparametric Methods (Optional)  
17 06/13

Demonstration using R (II) (Online, MS Teams)

[16+2教學規劃: Online Learning]
18 06/20
Final exam
Final exam

Textbook: Anderson et al., 2019, Statistics for Business & Economics (14th Edition), Cengage Learning Ltd. (ISBN: 0357114485). [滄海圖書代理]/【巨流政大書城

Anderson et al., 2019, Statistics for Business & Economics (14th Edition), Cengage Learning Ltd. (ISBN: 0357114485).

 

Evaluation Criteria:(Adjustments to the grading distribution require the agreement of the majority of the students in the class.)

  • Quiz:30% (Two times)。
  • Midterm exam:30%。
  • Final exam:30%
  • Attendance 10%。 (有到有分,沒到沒分,不管請假和任何因素)
  • Homework 0%。
  • TA class 0%
  • Extra: R Bonus Test (20%,two times,after the midterm exam and final exam。)
  • Adjustment of scores (up to 10 points): Based on class performance, learning attitude, etc. (Scores will not be adjusted for personal reasons). (Please note that the teacher will not respond to messages or emails requesting for score adjustments at the end of the semester. I appreciate your understanding!)
     

Notes (in class)

  • The regulations regarding absences and truancy will be handled according to the school rules.
  • The highest principle in class is "mutual respect", and students have the obligation to "inform the teacher" accordingly.
  • School's policy: Working definition of EMI: For EMI courses, the delivery of content, whole-class interaction, the learning materials, and the demonstration and assessment of learning outcomes (such as oral presentation, assignments, or tests) should be in English. Other languages may be used in a principled and limited way in specific circumstances, ... lecturers should ensure that at least 70% of class communication takes place in English.

Notes (exams)

  • All four exams will be held during regular class hours (quiz: 14:10~15:50, midtem/final exam: 13:10~15:50). Make-up exams are not allowed without a special reason. (Please report any special reasons in advance; if the teacher approves the make-up exam, it should be arranged with the TA within one week). Only one make-up exam is allowed. There is no make-up exam for the R programming bonus test.
  • The calculation method for make-up exam scores is: (original score - 60) x 0.7 + 60. For example, if the original score of the make-up exam is 80 points, then the make-up exam score is (80 - 60) x 0.7 + 60 = 74 points. If the original score of the make-up exam is less than 60 points, the original score will be used.
  • The exam questions will be in English. The type of questions for each exam are: 3~4 multiple-choice questions (15~20 points), 2~4 fill-in-the-blank questions (15~20 points), 2 short answer questions (20 points), and 2 calculation questions (40 points). (There may be some bonus questions, 10~20 points.)
  • A score greater than 100 points will be recorded as 100 points, and then multiplied by the percentage corresponding to the score.
  • Students caught cheating during the exam will not have any of their current and future exam papers and assignments graded by the teacher. In severe cases, the matter will be reported to the school for further action. (No cheating during the exam,不要作弊!)
  • If you have any questions about your grades, please contact the teacher within one week after the grades are announced.