Overview:
This course aims to provide comprehensive insights into fundamental statistical and
analytical techniques that are essential for data-driven decision making. The course
covers from basic descriptive statistics to more complex probabilistic theories and
data visualization techniques.
What You'll Learn
- Foundations of Descriptive Statistics: Understand how to summarize and describe essential features of data.
- Probability Theories and Their Applications: Explore fundamental probability concepts and how they apply to real-world data analysis.
- The Role of Big Data in Modern Analytics: Gain insights into what constitutes Big Data and its impact on analytics.
- Inferential Statistics for Decision Making: Learn to make predictions and inferences from data samples.
- Understanding Mean, Median, and Mode: Dive deeper into these measures of central tendency and when to use each.
- Exploring Measures of Spread: Understand variability in data using concepts like range, variance, and standard deviation.
- The Importance of Distribution Shapes: Learn about different distribution types and their implications in data interpretation.
- Effective Data Visualization Techniques: Master the art of presenting data visually to communicate information clearly and efficiently.