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)
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
