実戦力主義。の統計学 Excel統計学で見えなかったものが見えてくる。

Unlock Data Insights with Excel: A Practical Guide to Statistics

Discover the power of statistics and learn how to effortlessly apply it using Excel. This comprehensive course equips you with the skills to analyze data from diverse fields – including healthcare, education, economics, human resources, and disaster preparedness – revealing hidden patterns and valuable insights. Master the operation of powerful tools to transform raw data into actionable knowledge.

This course is structured into three parts:

Part 1: Foundations of Statistical Analysis (3 Sessions)

Build a strong understanding of core statistical concepts. We demystify key terms like statistical significance, sampling error, and Bayesian estimation.

• Understanding Statistical Significance: Explore how statistical significance differs from everyday usage. We'll use a captivating example – a sushi taste test comparing human-made and robot-made sushi – to determine how many rounds of a contest are needed to definitively declare one "significantly better."
• Managing Sampling Error: Learn how to interpret public opinion polls and other survey data with confidence. We'll explain how to calculate the necessary sample size to achieve a desired level of accuracy (±2.5%).
• Bayesian Estimation: Discover intriguing applications of Bayesian estimation using real-world examples like cancer screening and PCR testing.

Part 2: Data Analysis with Small Datasets (3 Sessions)

Dive into practical techniques for analyzing smaller datasets using Excel.

• Hypothesis Testing with Z-Tests: Analyze data from a Hawaiian population guessing quiz to understand the application of Z-tests and determine if there's a statistically significant difference in means.
• T-Tests: One-Sample & Independent Samples: Master t-tests for comparing means. We'll explore both one-sample t-tests, using data from Excel training effectiveness studies, and independent samples t-tests, analyzing data from an experiment on the effect of holding chopsticks to enhance creativity.
• Real-World Applications: Gain hands-on experience with data from actual experiments and surveys, making statistical analysis relatable and engaging.

Part 3: Big Data Analysis & Machine Learning (3 Sessions)

Explore advanced statistical techniques applicable to large datasets and their role in Artificial Intelligence (AI).

• Regression Analysis: Learn the fundamentals of regression analysis, a key component of machine learning.
  • Simple Linear Regression: Predict future trends using elderly pedestrian data published by the Japan Agency for Medical Research and Development (AMED).
  • Correlation Analysis (CS Analysis): Investigate factors influencing employee motivation using data from employee surveys. Discover practical strategies to boost morale.
  • Multiple Regression: Develop an AI interviewer that predicts a missing interviewer's score based on the remaining interviewers' evaluations – a fascinating application of multiple regression.
• Data-Driven Insights: All analyses utilize readily available and relatable data, including data from past Excel training programs and simulated interview data.
• Engaging Learning: We prioritize making statistics accessible and enjoyable, fostering a passion for data analysis and Excel.

New! Subtitles are now available for all videos (as of June 2021).