Course title
M30660001
Basic Statistics

 CETINKAYA AHMET
Middle-level Diploma Policy (mDP)
Program / Major mDP Goals
先進国際課程 A-1 A-1 Students shall obtain basic and advanced knowledge and skills in mathematics, natural and computer sciences as well as presentation skills to communicate on their knowledge with scholars from various fields.
(改組前)先進国際課程 A-1 A-1 Students shall obtain basic and advanced knowledge and skills in mathematics, natural and computer sciences as well as presentation skills to communicate on their knowledge with scholars from various fields.
Purpose of class
Students will understand and be able to apply methods of data description, probability distributions, inferential statistics, and linear models.
Course description
We can obtain various kinds of data through experiments, observations, or surveys. Statistics is one of the methods that can allow us to extract information from such data and understand the structure behind it. Statistical analysis methods have become increasingly important in recent years and they have been actively developed in various directions. The contents of this class are fundamental and have been used for a long time. Their understanding is thus important for handling data. In this class, students will learn how to use basic concepts and analytical methods of statistics.
Goals and objectives
  1. Students will be able to use methods of describing and summarizing data.
  2. Students will be able to utilize probability, probability distributions, and their relationship to data.
  3. Students will be able to apply inferential statistics to data.
  4. Students will be able to use hypothesis testing and apply it to data.
  5. Students will be able to use linear models and apply them to data.
Relationship between 'Goals and Objectives' and 'Course Outcomes'

 Assignments Mid-term exam Final exam Total.
1. 8% 12% 20%
2. 8% 12% 20%
3. 8% 6% 6% 20%
4. 8% 12% 20%
5. 8% 12% 20%
Total. 40% 30% 30% -
Evaluation method and criteria
Assignments will contribute to 40% of the grade; Midterm exam will contribute to 30% of the grade, and final exam will contribute to 30% of the grade. Those who get at least 60% of the full score will pass this course.
Language
English
Class schedule

 Class schedule HW assignments (Including preparation and review of the class.) Amount of Time Required
1. Methods of describing and summarizing data (variable types, histograms, and charts) Assignment 20minutes
2. Methods of describing and summarizing data (bivariate data, cross-tabulation, correlation) Assignment 20minutes
3. Events, probability, and probability distributions Assignment 20minutes
4. Random variables, expectation, variance, and probability distributions Assignment 20minutes
5. Sampling methods, statistical point estimation Assignment 20minutes
6. Continuous probability distributions, statistical interval estimation Assignment 20minutes
7. Mid-term exam with feedback through Moodle Review of Lectures 1-6 150minutes
Exam review 30minutes
8. Continuous probability distributions, one- and two-sample problems, covariance, correlation coefficient Assignment 20minutes
9. Statistical hypothesis testing (one-sample problems) Assignment 20minutes
10. Statistical hypothesis testing (two-sample problems), description of time-series data Assignment 20minutes
11. Linear regression models, interval estimation of regression coefficients, significance tests for linear regression Assignment 20minutes
12. Analysis of variance (one-way/two-way analysis) Assignment 20minutes
13. Normality, goodness-of-fit, and independence tests Assignment 20minutes
14. Final exam with feedback through Moodle Review of Lectures 8-13 175minutes
Exam review 30minutes
Total. - - 625minutes
Feedback on exams, assignments, etc.
ways of feedback specific contents about "Other"
The Others Feedback through Moodle.
Textbooks and reference materials
Textbook (in Japanese): Basic Statistics (compatible with Statistics Test Level 2), Japan Statistical Society, Tokyo-Tosho, 2015, (in Japanese).

Optional reference for self-study (in English): Statistics, R. S. Witte, J. S. Witte, Wiley, 2017 (11th edition).
Prerequisites
There are no prerequisites.
Office hours and How to contact professors for questions
  • By appointment. Contact e-mail address: ahmet@shibaura-it.ac.jp
Regionally-oriented
Non-regionally-oriented course
Development of social and professional independence
  • Course that cultivates an ability for utilizing knowledge
Active-learning course
N/A
Course by professor with work experience
Work experience Work experience and relevance to the course content if applicable
N/A N/A
Education related SDGs:the Sustainable Development Goals
  • 4.QUALITY EDUCATION
Last modified : Sat Mar 14 13:43:56 JST 2026