Revisiting Statistical Foundations: A Summary of My 2017 and 2020 Course Content

## Table of Contents
1. [Basic Concepts of Statistics](#1-basic-concepts-of-statistics)  
   - [Fundamental Theory of Statistics](#fundamental-theory-of-statistics)
   - [Data Collection and Quality Control](#data-collection-and-quality-control)
2. [Data Analysis Using Excel](#2-data-analysis-using-excel)  
   - [Basic Excel Operations](#basic-excel-operations)  
   - [Data Visualization](#data-visualization)  
   - [Basic Statistical Analysis](#basic-statistical-analysis)  
3. [Advanced Analytical Techniques](#3-advanced-analytical-techniques)  
   - [Random Numbers and Simulations](#random-numbers-and-simulations)  
   - [Cross-Tabulation of Data](#cross-tabulation-of-data)  
4. [Practical Applications and Career Aspirations](#4-practical-applications-and-career-aspirations)  

## 1. Basic Concepts of Statistics
Through university courses, I learned the foundational theories and practical methods of statistics. Below are the key points I covered:

### Fundamental Theory of Statistics
● **Purpose and Importance of Data Analysis**  
The goal of studying statistics is to collect data, analyze it, and make decisions based on the results. Through this, I learned methods to derive valuable insights from data.

● **Types of Data and Measurement Scales**  
Data is mainly divided into "discrete data" and "continuous data," and different analysis techniques are required for each. I also learned about different measurement scales: nominal, ordinal, interval, and ratio scales, and understood their differences.

### Data Collection and Quality Control
● **Survey Design**  
I learned how to design surveys effectively, including choosing between single-choice or multiple-choice questions and methods to increase respondent engagement.
● **Data Quality Management**  
I studied how to manage the quality of primary and secondary data and methods to minimize errors. Practical exercises were conducted to check the quality of real data.

## 2. Data Analysis Using Excel
In my courses, a significant focus was placed on using Excel for data analysis. The following topics were covered:

### Basic Excel Operations
● **Cell Input and Calculations**  
I learned the basic operations in Excel, including how to use functions and formulas and how to handle spreadsheet operations.

### Data Visualization  
● **Creating Graphs**  
I learned how to visually represent data using Excel by creating graphs (bar graphs, line graphs, histograms, etc.). This is an essential skill to easily understand data trends.

### Basic Statistical Analysis  
● **Calculating Mean, Median, Variance, and Standard Deviation**  
I learned how to compute basic statistical measures and understand the variability and trends of data.

● **Chi-Square Test and Correlation Analysis**  
I studied how to use the chi-square test for independence testing and correlation analysis to explore relationships between variables. This helped me develop skills to validate correlations and significance in data.

## 3. Advanced Analytical Techniques  

### Random Numbers and Simulations  
● **Simulation with Random Numbers**  
I learned how to generate random numbers and conduct simulations using Excel's analysis tools. This deepened my understanding of probability theory and statistical testing.

### Cross-Tabulation of Data  
● **Cross-Tabulation and Pivot Tables**  
I learned how to perform cross-tabulation and analyze data combinations using pivot tables in Excel. This technique is crucial for efficiently summarizing and analyzing large datasets.

## 4. Practical Applications and Career Aspirations  
The statistical knowledge and analytical techniques I learned are highly applicable in practical settings. Data-driven decision-making is essential in various fields such as business, marketing, and research.

Studying at an overseas university also helped me develop an international perspective.

Through my hands-on experience in public relations and marketing communications, I developed a strong interest in applying data analysis to solve business problems.

I am eager to take on roles where I can analyze data, measure performance, and derive actionable insights to support business decision-making.

My goal is to develop advanced analytical skills to provide data-driven recommendations that optimize performance and strategy. I am actively enhancing my expertise and look forward to applying these skills in a professional setting.