B3101
統計基礎
INTRODUCTION TO STATISTICS 		基盤科目-データサイエンス科目-データサイエンス１
Fundamental Subjects - Subjects of Data Science - Data Science 1
2 単位
実施形態 完全オンライン
開催日程 秋学期 火曜日４時限
担当教員 トレース， ジョナサン Ｗ（トレ-ス ジヨナサン）
関連科目
開講場所 SFC
授業形態 講義、グループワーク
履修者制限

履修人数を制限する

受入学生数（予定）：約 25 人
選抜方法：課題提出による選抜

【課題内容】 選抜課題の参考資料
Please download the attached form, read the instructions and complete the linked survey within. When you are finished, submit your form with the appropriate information no later than September 28th, 17:00. Results will be announced shortly after.



Note: Depending on the amount of interest, not everyone may be able to join the class. Only those students who complete the required screening will be accepted into the class if openings become available.

◯エントリー〆切日時：2020年9月28日（月） 17:00
◯履修許可者発表日時：2020年9月30日（水） 17:00

◯ファイル登録

Only the selected students can take this course.

Number of students in the class (scheduled) : About 25
Pre-registration screening by submitted an assignment

【ASSIGNMENT】 Reference Material for Assignment
Please download the attached form, read the instructions and complete the linked survey within. When you are finished, submit your form with the appropriate information no later than September 28th, 17:00. Results will be announced shortly after.



Note: Depending on the amount of interest, not everyone may be able to join the class. Only those students who complete the required screening will be accepted into the class if openings become available.

* Schedule: TBD
履修条件

Academic Level English

「データサイエンス基礎」の単位を修得していること。またはデータサイエンス科目認定試験に合格していること。

In order to register the Subjects of Data Science, students need to earn credits for "Basics of Data Science" or pass the "Data Science Qualification Examination"
使用言語 英語
連絡先 tracej@sfc.keio.ac.jp
授業ホームページ
同一科目

学生が利用する予定機材/ソフト等

Laptop with Statistical Software (SPSS, SAS) required for assignments & tests.
設置学部・研究科 総合政策・環境情報学部
大学院プロジェクト名

大学院プロジェクトサブメンバー

ゲストスピーカーの人数 0
履修選抜・課題タイプ=テキスト登録可 false
履修選抜・選抜課題タイプ=ファイル登録可 true
GIGAサティフィケート対象 true
最終更新日 2020/09/03 18:44:10

科目概要

This class will teach the fundamentals of working with and interpreting data. It assumes no knowledge of statistics. We will focus on concepts, procedures, and best practices, with an eye toward real-world use of these methods in your research and/or career. This section is especially recommended for students who THINK they are bad at math.

Specific topics we will cover are: Types of data, data gathering, data description/summary, analyses of relationships, probability, hypothesis testing, and analyses of differences.

NOTE: This class will be held primarily On-Demand, supplemented by short (~20 minute) Q&A sessions over Zoom each week. All lectures, assignments, and tests will only be available online and are to be completed individually each week.

この授業で、データの操作と解釈の基礎を習得します。統計学を勉強したことのない学生を対象としています。学生の研究やキャリアに活用出来ることを目的として、統計学の概念・手法・ 最良の実践を中心に授業を展開していきます。「数学が苦手」と思っている学生に特に勧められます。

具体的に、データの種類・データ収集・データの記述・関係の分析・確率・仮説検定・相違の分析を扱います。

授業シラバス

主題と目標／授業の手法など

This class will teach you how to think about data, how to run and analyze quantitative analyses using statistical tools, and how to interpret results in simple terms.

This course will be task-based, and so it is essential that students complete all of the readings and assignments. Weekly quizzes will address technical aspects of the statistical methods used, hands-on assignments will address critical thinking and application skills, and tests will measure the acquisition of both.

NOTE: This class will be held primarily On-Demand, supplemented by short (~20 minute) Q&A sessions over Zoom each week. All lectures, assignments, and tests will only be available online and are to be completed individually each week.

教材・参考文献

Veaux, R. D. D., Velleman, P. F., & Bock, D. E. (2013). Stats: Pearson New International Edition: Data and Models. Pearson. (REQUIRED)
4th Edition (Digital Versions are OK, as long as it's 4th edition)

提出課題・試験・成績評価の方法など

Online Module Completion & Participation 25%
Weekly Online Quizzes 25%
Unit Tests 50%

履修上の注意

This class will be taught in English, and the readings require advanced reading comprehension in academic English. Likewise, assignments require academic-level writing in English.

This class assumes NO training in statistics and is intended to impart to you a strong foundation in key concepts upon which you can build throughout your studies.

While this is a DS1 class, the content of the course is recommended for students in their second year of study as they presumably will have more defined research goals and practical applications for the methods learned in class.

授業計画

第1回 Introduction to the Course

Overview of the topics and the course
(First Meeting via Zoom! Details provided on SFC-SFS)

第2回 Exploring & Understanding Data (1)

Kinds of data and how to present and summarize them
(On-demand + Zoom Q&A Session)

第3回 Exploring & Understanding Data (2)

Randomness, surveys, and experiments*

第4回 Exploring & Understanding Data (3)

Distributions, the standard deviation, and the normal model
(On-demand + Zoom Q&A Session)

第5回 Analyzing Relationships (1)

Correlations
(On-demand + Zoom Q&A Session)

第6回 Analyzing Relationships (2)

Linear Regression
(On-demand + Zoom Q&A Session)

第7回 Randomness & Probability (1)

Sampling
(On-demand + Zoom Q&A Session)

第8回 Randomness & Probability (2)

Basic Probability*

第9回 Randomness & Probability (3)

Binomials
(On-demand + Zoom Q&A Session)

第10回 Hypothesis Testing (1)

Samples, Errors, & Sampling Distributions
(On-demand + Zoom Q&A Session)

第11回 Hypothesis Testing (2)

Confidence Intervals & Significance*

第12回 Hypothesis Testing (3)

Error, Power, & Effect Size
(On-demand + Zoom Q&A Session)

第13回 Analyzing Differences (1)

Means Comparisons Using T-tests
(On-demand + Zoom Q&A Session)

第14回 Analyzing Differences (2)

Comparing means when you have more than 2 groups (ANOVA)
(On-demand + Zoom Q&A Session)

第15回 Analyzing Differences (3)

Comparing Frequencies Using Chi-Square & Final Review
(On-demand + Zoom Q&A Session)

15回目に相当するその他の授業計画

Extra study session for the final.
Your day to ask me anything you still don't understand for the final exam.