Basic Statistics with Excel

The logic behind basic statistical theory and statistical testing,
Understand while implementing it in Excel 🔦

Lecture Topics 📖

Statistics classes in school are so hard to understand, aren't they? Especially the ones about tests, no matter how many times you hear about them, they're still confusing! The truth is, statistics is difficult because we lack a basic understanding of the underlying theories behind them. Once you understand the background of statistical tests and study them, nothing is more fun than statistics! :)

In this course, you'll learn the properties of basic statistical indicators , the laws of large numbers and the central limit theorem, fundamental statistical concepts , and establish a solid understanding of confidence intervals, statistical significance levels, and p-values . This course is filled with my teaching expertise, accumulated while teaching basic statistics to undergraduates at American universities. Statistics can be difficult, but we make it fun.

I recommend this to these people 🙋‍♀️

Someone who feels better when they implement something themselves

People who learn by giving specific examples when studying

Those who don't understand basic statistics and just memorize and solve problems

For those who want to know why they learn statistical theory

What you'll learn 📚

1) Random variables and samples
We'll create random variables ourselves and learn about their properties. This will establish concepts about random variables and sampling. We'll use the RAND() function to create virtual coins and learn about Bernoulli random variables.

2) Data visualization tools
Learn how to visualize given data in Excel. Learn about pie charts, histograms, scatter plots, and more.

3) Statistical indicators that capture the center and spread of data
Learn statistical indicators that capture the characteristics of data distributions. You'll explore concepts such as mean, median, IQR, and variance. Understand the concepts of expected value and variance of random variables through visualization.

Learn about boxplots, which visualize the characteristics of a distribution using learned statistical indicators.

4) Digging into random variables
We will learn about the characteristics of random variables. We will deepen our understanding of random variables by understanding the concept of parameters and visualizing each concept. We will establish the concepts of random variables and samples and understand the laws of large numbers.

5) Building a foundation based on statistical inference
We will focus on understanding the central limit theorem, a fundamental principle of statistical inference. We will also study the properties of the normal distribution and learn how to calculate probability.

6) Understanding statistical inference
Gain a deeper understanding of confidence intervals and the statistical estimation process.

7) Understanding statistical tests
Learn statistical testing terminology and implement the entire process to understand the statistical testing process. Learn about statistical significance levels, rejection thresholds, p-values, and more.

Expected Questions Q&A 💬

Introducing the Knowledge Sharer ✒️

I'd like to share what I've learned and realized while studying statistics with those of you who are following my path. I hope this lecture will be a helpful resource, answering some of your questions. I also hope that for those who are following my path, I hope my footsteps will offer some comfort.

History

• Representative of Wise Statistics Life
• (Current) Lecturer in Statistics at Korea University of Engineering and Technology
• (Current) Samsung DS Division New Employee Job Training Basic Statistics Instructor
• (Former) Lecturer in Applied Statistics and Actuarial Risk Management at the Graduate School of Actuarial Science, Sungkyunkwan University

Academic background

• The University of Iowa, Statistics & Actuarial Science PhD Program (ABD)
• Master's degree in Actuarial Science from Sungkyunkwan University
• Bachelor of Science in Statistics and Industrial Engineering from Sungkyunkwan University