Course curriculum

    1. 1710 Correlation and Regression

    1. OneNote Recourse

    2. 1711 Perfect Positive Correlation

    3. 1719 Perfect Negative Correlation

    4. 1726 Correlation Simple Few Data Points Example

    5. 1731 Correlation Random Number Generation Example

    6. 1741 Correlation Calculation with Strange Result

    7. 1751 Correlation Large Data Sets Focus of Z Score Relationship95be444.autosave

    8. 1761 Correlation Baseball Statistics

    1. 1710 Perfect Positive Correlation

    2. 1712 Perfect Positive Correlation Part 2

    3. 1718 Perfect Negative Correlation

    4. 1725 Correlation Simple Low Data Points Example

    5. 1730 Correlation Random Number Generation Example

    6. 1732 Correlation Random Number Generation Example Part 2

    7. 1740 Correlation Calculation with Strange Result

    8. 1750 Correlation Large Data Sets Focus of Z Score Relationship Part 1

    9. 1752 Correlation Large Data Sets Focus of Z Score Relationship Part 2

    10. 1760 Correlation Baseball Statistics

    11. 1762 Correlation Baseball Statistics Part 2

About this course

  • $49.99
  • 20 lessons
  • 7 hours of video content

Description

Welcome to this statistics & Excel course where we unravel the complexities of statistical relationships and predictive modeling, all while harnessing the power of Microsoft Excel. This course is meticulously designed for those who aspire to gain a profound understanding of correlation, regression, and the vital role they play in data analysis.

We start our journey by dissecting the concept of Correlation, exploring its types and implications, and emphasizing that correlation does not imply causation. Through illustrative examples like the relationship between height and weight, and ice cream sales with temperature, we make these concepts tangible. Excel plays a crucial role here, as we employ its tools to calculate the Correlation Coefficient (r), helping us quantify the strength and direction of linear relationships.

Delving deeper, we introduce Scatter Plots, a pivotal tool in visualizing data relationships. Participants will learn to create and interpret scatter plots in Excel, identifying linear patterns and understanding when there might be no correlation at all. This visual prowess sets the stage for our next big topic: Regression.

Why use Regression? This course answers the question by guiding students through the principles of Simple Linear Regression, using Excel to model the relationship between two variables. We explore the concept of Residuals, emphasizing the goal of minimizing these values through the Least Squares Method, all performed seamlessly within Excel.

However, we don't stop at just building models. The course instills a critical understanding of why "Correlation ≠ Causation," exploring spurious correlations and highlighting the importance of not misinterpreting data relationships. Engaging examples and Excel exercises ensure that these lessons are not just learned, but also applied.

By the end of this course, students will not only master the concepts of correlation and regression but also excel in utilizing Excel as a powerful tool for statistical analysis and predictive modeling. Join us to embark on this enlightening journey, and transform your understanding of data relationships and the art of prediction.