Correlation -Stats

https://canvas.liberty.edu/courses/962521/pages/watch-correlation-through-dance?module_item_id=91232347

https://canvas.liberty.edu/courses/962521/pages/watch-the-correlation-coefficient-explained-in-3-steps?module_item_id=91232351

https://onlinestatbook.com/2/describing_bivariate_data/restriction_demo.html#video

Module 7: Week 7 Introduction

Overview

Correlation is your introduction to predictive thinking. This module you will be working with ideas related to applying correctional techniques.

Learning Outcomes

Upon successful completion of this module, you will be able to:

· Understand correlation conceptually.

· Interpret the strength direction of correlations relative p-values, experiment wide error and the null hypothesis.

· Use SPSS to conduct correlational analysis, create scatterplots, and interpret results.

· Understand the coefficient of determination and how it relates to other descriptions of effect.

· Understand the effect of third variables and proper specification of the model.

Be sure to complete all Introduction, Learn, and Apply items in  Module 7: Week 7 - Correlation by Sunday 11:59 p.m. (ET) on the assigned due date. Use the Modules link on the left side of the screen at any time to view your progress in the course.

EDCO 735

Essay: Correlation Assignment Prompts

· Provide an example of a hypothetical situation in which a Pearson’s  r is used. Explain how the sign and magnitude of  r would contribute to a researcher’s understanding of the relationship between X and Y. Given the assumptions for use of Pearson’s  r, what would a thorough data screening entail to use of (think statistical tests and data visualization)? How might a researcher attempt to decrease the risk of a Type I error while reporting several correlations? 

· Discuss the two forms of the regression equation, raw score and z score, and provide examples of situations in which one would be more useful than the other. Explain how  r,  R, and  B are related to one another in bivariate regression.