Fundamentals of Statistical Methods

Course Description: Chapter 1 – Statistical Methods

This chapter introduces the fundamental concepts of Statistics, a branch of mathematics that focuses on collecting, organizing, analyzing, and interpreting numerical data for decision-making. It provides an essential foundation in both Descriptive Statistics and Inferential Statistics:

1. Descriptive Statistics: Learn to summarize and interpret raw data using measures like central tendency, dispersion, skewness, and kurtosis.
2. Inferential Statistics: Gain skills to make predictions about a population based on sample data.

Key highlights of this chapter include:

1.1 Measures of Central Tendency

Understand how to calculate the central value of a dataset using:

• Arithmetic Mean (Simple and Weighted Mean)
• Median (for discrete and continuous data)
• Mode (including the empirical relationship between mean, median, and mode)
• Geometric Mean
• Harmonic Mean

1.2 Arithmetic Mean

Master techniques to compute arithmetic mean for discrete and continuous data and explore its properties, such as its effect under origin and scale transformations.

1.3 Median

Learn the method to calculate the median for discrete and continuous datasets and its significance in data interpretation.

1.4 Mode

Study the modal value, its calculation, and its importance in datasets with frequently recurring values.

1.5 Geometric Mean and Harmonic Mean

Explore advanced measures of central tendency and their applications in datasets where relationships between numbers matter.

By the end of this chapter, you will have a strong grasp of statistical methods to effectively organize and summarize data, providing the foundation for further exploration into advanced statistical techniques.

Prerequisites: Basic algebra and an understanding of mathematical notation.