Introduction to Statistics (English Edition)
What you'll learn
- Descriptive Statistics (Median/Mean/Variance/Standard Deviation/Standardization)
- Probability Distributions (Probability Models/Binomial Distribution/Normal Distribution)
- Point Estimation (Point Estimates of Population Mean and Population Variance)
- Interval Estimation I (Interval Estimation of the Population Mean)
- Interval Estimation II (T-Distribution/Central Limit Theorem)
- Interval Estimation III (Interval Estimation of the Population Proportion)
- Hypothesis Testing (Process of Hypothesis Testing/Testing of Population Mean)
Requirements
- No specific requirements
Description
This is a basic course designed for us to efficiently learn the fundamentals of statistics together!
(The English version* of the statistics course chosen by over 28,000 people in the Japanese market!")
*Note: The script and slides are based on the original version translated into English, and the audio is generated by AI.
"Let's make sure to standardize the data and check its characteristics."
"Could we figure out the confidence interval for this data?"
"Let's check if the results of this survey can be considered statistically significant."
In the business world, there are many situations where statistical literacy becomes essential.
With the widespread adoption of AI/machine learning and a strong need for DX/digitalization, these situations are expected to increase.
This course is aimed at ensuring we're well-equipped with statistical literacy and probabilistic thinking to navigate such scenarios.
We'll carefully explore the basics of statistics, including "probability distributions, estimation, and hypothesis testing."
By understanding "probability distributions," we'll develop a statistical perspective and probabilistic thinking.
Learning about "estimation" will enable us to discuss populations from data (samples), and grasping "testing" will help us develop statistical hypothesis thinking.
This course is tailored for beginners in statistics and will explain concepts using a wealth of diagrams and words, keeping mathematical formulas and symbols to the minimum necessary for understanding.
It's structured to ensure that even beginners can learn confidently.
Let's seize this opportunity to acquire lifelong knowledge of statistics together!
(Note: Please be aware that this course does not cover the use of tools or software like Excel, R, or Python.)
What we will learn together:
Basic statistical literacy Knowledge of "descriptive statistics" in statistics
Understanding of "probability" and "probability models" in statistics
Understanding of "point estimation" and "interval estimation" in statistics
Understanding of "statistical hypothesis testing" in statistics
Comprehension of statistics through abundant diagrams and explanations
Visual imagery related to statistics
Reinforcement of memory through downloadable slide materials
Who this course is for:
- New to statistics
- Tried to learn statistics but gave up
- Wish to relearn statistics from the basics
- Curious about what statistics is like
- Frequently deal with data in business
- Want to organize fragmented knowledge of statistics
- Prefer to understand through diagrams and words rather than formulas and symbols
- Want to learn statistics but don't have time to study textbooks
Instructor
- 4.4 Instructor Rating
- 16,153 Reviews
- 66,702 Students
- 15 Courses
Miyamoto Shota: 講師 / リサーチャー
DXの時代に不可欠となるデータ分析に関する学びを基礎からわかりやすく提供していきます。
独学でデータ分析を学んだ後、シンクタンク在籍中に統計学や機械学習を基礎から丁寧に学び直しています。
基礎的な内容への深い理解をベースとしながら、独学における苦労や難所に関する理解を踏まえ、初心者でもわかりやすく学べるようなコース設計を心がけています。
この機会にぜひ一緒にデータ分析を学んで一生モノのスキルを身につけていきましょう！！
《経歴》
慶應義塾大学法学部卒業後、大手インフラ企業を経て国内シンクタンクにてデータ分析やリサーチ活動に従事。公的統計データやマーケティングデータの分析に加え、統計的手法や機械学習モデルを用いた需要予測、売れ行き要因分析等のリサーチ活動を行ってきました。その後、国内MBAを取得、現在は会社を設立しリサーチ活動や講師業を行っています。
********************
In the era of digital transformation, I am committed to providing a clear and foundational understanding of data analysis, an indispensable skill set. After self-learning data analysis, I revisited statistics and machine learning from the ground up while at a think tank.
With a deep understanding of the basics, I design courses that are accessible to beginners, taking into account the struggles and challenges of self-learning. Let's learn data analysis together and acquire a skill set that will last a lifetime!
Background:
After graduating from the Faculty of Law at Keio University, I worked at a major infrastructure company, before engaging in data analysis and research activities at a domestic think tank. I have conducted research activities including analysis of public statistical data and marketing data, as well as demand forecasting and sales factor analysis using statistical methods and machine learning models. Following this, I obtained an MBA in Japan and currently run my own company, focusing on research activities and teaching.