Statistical Foundations for Artificial Intelligence

📚 Course Title: Analyzing Data: Exploring Moments, Skewness, Kurtosis & Inferential Statistics: Making Sense of Data

Course Description:

Embark on a comprehensive journey into the world of Statistics with our online course, "Analyzing Data: Exploring Moments, Skewness, Kurtosis & Inferential Statistics: Making Sense of Data." This course is tailored for students of Applied Mathematics or Statistics, as well as anyone with an interest in deepening their understanding of Statistics. A robust grasp of Statistics is crucial for fields like Economics and Actuarial Sciences, and this course will equip you with the necessary skills.

What You'll Learn:

Moments of a Distribution 📈

• Moments: Dive into the world of moments—a fundamental concept in probability theory and statistics. We'll focus on the first four moments, known as central moments, which play a crucial role in describing the behavior of a distribution.
• Calculating Moments: Learn how to calculate the first 4 central moments for various distributions and understand their significance in a frequency distribution context.

Skewness & Kurtosis 📊

• Skewness and Kurtosis Explained: Understand what skewness and kurtosis are, why they matter, and how they impact the shape of your data's distribution.
• Karl Pearson's Coefficient of Skewness: Learn to calculate Karl Pearson's coefficient of skewness for a frequency distribution using given mean, mode, and standard deviation values.
• Bowley's Coefficient of Skewness: Discover Bowley's method of measuring skewness and how to apply it to a frequency distribution.
• Kurtosis: Explore the concept of kurtosis, learn about mesokurtic, leptokurtic, and platykurtic distributions, and practice calculating the 4th central moment for different types of distributions.

Correlation & Rank Correlation 🌐

• Correlation Coefficient: Grasp the concept of correlation as a measure of the relationship between two variables. Learn how to calculate covariance and standardize it using Karl Pearson's coefficient of correlation.
• Rank Correlation: Understand Spearman's Rank Correlation and how to calculate it when dealing with ranked data. Discover what happens when ranks are repeated!

Inferential Statistics 🔍

• Basic Introduction: Get a foundational understanding of terms like sample mean, sample proportion, and sample standard deviation. Learn about interval estimation and its significance in inferential statistics.
• Confidence Intervals & Values: Dive into the world of confidence intervals and learn how to calculate interval estimations for population means and proportions.
• Hypothesis Testing: Explore the process of hypothesis testing, understand the role of the null hypothesis, and learn the parameters that guide accepting or rejecting it.

t Distributions & Hypothesis Testing 📑

• t Distributions: Learn how to calculate t values using tables and understand their role in hypothesis testing. Gain insight into two-tailed t tests and their application.

Why Take This Course?

• Practical Skills: Develop practical skills that are highly valued in various fields, including Economics and Actuarial Sciences.
• Real-World Problems: Apply your knowledge to solve real-world problems using statistical methods and techniques.
• Interactive Learning: Engage with interactive content that makes learning statistics both effective and enjoyable.
• Career Enhancement: Strengthen your resume and career prospects by mastering these essential statistical tools.

Join Us Today! 🚀

Enroll now and take the first step towards becoming a data analysis expert. With this course, you'll not only understand the 'why' but also the 'how' of analyzing data, making sense of statistics, and unlocking insights from your datasets. Let's embark on this statistical adventure together! 🎓