Course curriculum

    1. 1610 Normal Distribution Bell Shaped Curve Gaussian Curve

    1. OneNote Recourse

    2. 1611 Bell Curve – Test Score Example

    3. 1621 Normal Distribution – Heights of Baseball Players Data545849f.autosave

    4. 1627 Bell Curve-People Weight Example

    5. 1633 Normal Distribution – Calories Example

    6. 1639 Bell Curve Batting Average Comparison

    1. 1610 Bell Curve – Test Score Example Part 1

    2. 1612 Bell Curve – Test Score Example Part 2

    3. 1614 Bell Curve – Test Score Example Part 3

    4. 1620 Normal Distribution – Hights of Baseball Players Data

    5. 1622 Normal Distribution – Hights of Baseball Players Data Part 2

    6. 1626 Bell Curve-People Weight Example Part 1

    7. 1628 Bell Curve-People Weight Example Part 2

    8. 1632 Normal Distribution – Calories Example

    9. 1634 Normal Distribution – Calories Example Part 2

    10. 1638 Bell Curve Batting Average Comparison

    11. 1640 Bell Curve Batting Average Comparison Part 2

About this course

  • $49.99
  • 18 lessons
  • 8.5 hours of video content

Description

Embark on a comprehensive and in-depth journey into the fascinating world of the Gaussian or Normal Distribution, a cornerstone of statistical analysis and a critical tool for researchers, scientists, and analysts across diverse domains. This course, meticulously crafted for undergraduate students and professionals alike, unveils the layers of the Gaussian Distribution, elucidating its foundational role, intrinsic properties, and multifaceted applications.

Tracing the historical footsteps of the great mathematician Carl Friedrich Gauss, we explore his groundbreaking work and the subsequent emergence of the Gaussian Distribution as a pivotal tool in statistical studies. From predicting the position of celestial bodies to its modern-day applications in quality control and finance, the course paints a vivid picture of the distribution's significance and evolution.

Dive deep into the characteristics and properties of the Normal Distribution, learning to navigate its bell-shaped curve and symmetrical nature. Understand the critical roles of mean and standard deviation, and how they shape and define the distribution. Delve into the specifics of the Standard Normal Distribution, mastering the use of z-scores for standardizing and interpreting data.

Explore the intricacies of areas under the curve, and how they translate into probabilities and meaningful interpretations. The course provides a robust understanding of why the Gaussian Distribution arises so frequently in nature and statistics.

Through a myriad of practical examples, from the distribution of physical traits in populations to the analysis of sports statistics and outcomes in games of chance, the course demonstrates the ubiquity of the Gaussian Distribution.

This course is not just a statistical endeavor; it is a journey of discovery, insight, and application. It empowers students and professionals to not just understand the Gaussian Distribution but to wield it as a powerful tool in their analytical arsenal.