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2019　Statistics B

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Academic unit or major
Humanities and social science courses
Instructor(s)
Kezuka Kazuhiro 
Class Format
Lecture     
Media-enhanced courses
Day/Period(Room No.)
Mon1-2(S011)  Thr1-2(S011)  
Group
-
Course number
LAH.T201
Credits
2
Academic year
2019
Offered quarter
2Q
Syllabus updated
2019/3/18
Lecture notes updated
-
Language used
Japanese
Access Index

Course description and aims

Inferential statistics is the tool to grasp the information of population using the survey data. This tool is essential for analysis of social surveys and big data. Students learn inferential statistics with topics of social sciences, especially social inequality.

Student learning outcomes

At the end of this course, students will be able to:
1) understand and utilize the concept of test and estimation,
2) build probability models of social statistics or events.

Keywords

descriptive statistics, inferential statistics, probability distribution, sampling, estimation, hypothesis testing, regression analysis

Competencies that will be developed

✔ Specialist skills Intercultural skills Communication skills Critical thinking skills ✔ Practical and/or problem-solving skills

Class flow

The instructor will lecture about inference statistics based on the textbook. Students should solve some problems and submit their answers at the end of each class. At the end of term, students must take the final exam.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Introduction Understand the importance of estimation and test.
Class 2 Descriptive statistics Understand descriptive statistics.
Class 3 Gini coefficient Understand how to grasp the inequality.
Class 4 Mobility table Understand how to grasp the maintain of intergenerational inequality.
Class 5 Standard error and random sampling Understand the relationship between standard error and random sampling.
Class 6 Binomial distribution Understand binomial distribution and how to build probability model.
Class 7 Normal distribution Understand normal distribution and Central Limit Theorem.
Class 8 Point estimation and interval estimation Understand the logic of estimation.
Class 9 Unbiased estimator Understand unbiased estimator.
Class 10 Statistical test Understand the logic of test.
Class 11 Testing the difference of means Understand how to test the difference of means.
Class 12 Chi-squared test Understand Chi-squared test for cross table.
Class 13 Analysis of variance Understand analysis of variance.
Class 14 Test of correlation and t test Understand test of correlation and t test.
Class 15 Regression analysis Understand regression analysis

Textbook(s)

Textbooks will be specified by the instructor.

Reference books, course materials, etc.

Textbooks will be specified by the instructor.

Assessment criteria and methods

Students’ course scores are based on class reports 30% and the final exam 70%.

Related courses

  • LAH.T101 ： Statistics A
  • LAH.T301 ： Statistics C
  • LAH.S434 ： Essence of Humanities and Social Sciences38:Statistics

Prerequisites (i.e., required knowledge, skills, courses, etc.)

No prerequisites.

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