SemesterFall Semester, 2023
DepartmentMA Program of Sociology, First Year PhD Program of Sociology, First Year MA Program of Sociology, Second Year PhD Program of Sociology, Second Year
Course NameIntroduction to Statistical Analysis
InstructorKUAN PING-YIN
Credit3.0
Course TypeElective
Prerequisite
Course Objective
Course Description
Course Schedule
























































































































Week



Topic



Content and Reading Assignment



Teaching Activities and Homework



1



Course Introduction



 



Lecture



2



Statistics and Social Research



Ch. 1



Lecture; In-class Discussion; Homework



3



Basic Descriptive Statistics I



Ch. 2



Lecture; In-class Discussion; Homework



4



Descriptive Statistics II



 



Ch. 3



Lecture; In-class Discussion; Homework



5



R Lesson I



 



Lecture; In-class Discussion



6



Probability Distribution I



Ch. 4



Lecture; In-class Discussion; Homework



7



Probability Distribution II



Ch. 4



Lecture; In-class Discussion; Homework



8



1st Quiz & Review



 



Quiz



9



Estimation



Ch. 5



Lecture; In-class Discussion; Homework



10



Statistical Inference I



Ch. 6



Lecture; In-class Discussion; Homework



11



Statistical Inference II



Ch. 6



Lecture; In-class Discussion; Homework



12



2nd Quiz & Review



 



Quiz



13



Comparison of Two Groups



Ch. 7



Lecture; In-class Discussion; Homework



14



Analyzing Association between Categorical Variables



Ch. 8



Lecture; In-class Discussion; Homework



15



Comparing Groups: ANOVA I



Ch. 12



Lecture; In-class Discussion; Homework



16



Linear Regression and Correlation



Ch. 11



Lecture; In-class Discussion; Homework



17



Linear Regression and Correlation II



Ch. 11



Lecture; In-class Discussion; Homework



18



Final Exam



 



Quiz




 


Teaching Methods
Teaching Assistant

TBA


Requirement/Grading

Attendance:

Class attendance is required. Unlike some other courses, statistics requires you to gradually but constantly build your knowledge and skills. It is very difficult to catch up once you get behind. You are also expected to contribute to the class by asking questions, participating in class discussions, and working with each other on in-class exercises. Therefore, your attendance is essential for making these contributions.



Reading Assignments:

You are expected to read the assigned chapters before you come to each session. In order to successfully complete reading assignments, you need to understand what is in each chapter. In addition to highlighting the text and taking notes, I suggest you write down any specific questions.

You may find some chapters challenging to follow. Don't worry if this happens. It is important to finish reading the assigned chapter before each session to get a general idea about the chapter and go back to it after class to make sure that you understand the materials better.





Homework Assignments:

Learning by doing is very important for your understanding of statistics. There will be exercise questions given to you at the end of most sessions. You will have at least a week to complete each assignment. If you start working on your assignments early, you will have a chance to ask questions in the next class session before submitting your assignments.

I will collect assignments at the beginning of the scheduled class sessions (or you may submit assignments to Moodle in MS Word format). If you turn in your assignments late (anytime after the class session starts and before 4:00 pm on the next day), you will lose points. Where to submit late assignments: To be arranged by the TA.



Honor Code:

Please help each other, by all means, to exchange notes for missed class sessions, study for exams, etc. The assignments that you turn in should be your own work, however. Any form of violation will result in a "zero" for that particular assignment or an "F" for the course, at my discretion.



Grading:

Homework Assignments: 50%

Tests (3 tests including final): 45%

Attendance: 5%


Textbook & Reference

1. Agresti, Alan 2018. Statistical Methods for the Social Sciences. UpperSaddle River, NJ: Pearson  International Education. https://www.pearson.com/us/higher-education/program/Agresti-Statistical-Methods-for-the-Social-Sciences-5th-Edition/PGM334444.html

2. Navarro, Danielle. Learning Statistics with R. https://learningstatisticswithr.com/


Urls about Course
Attachment