Learning Objectives

Chapter 4

These are the learning objectives for this portion of the class:

  1. Define “bivariate data”
  2. Define “scatter plot”
  3. Distinguish between a linear and a nonlinear relationship
  4. Identify positive and negative associations from a scatter plot
  5. Describe what Pearson’s correlation measures
  6. State the values that represent perfect linear relationships
  7. State the relationship between the correlation of Y with X and the correlation of X with Y
  8. State why Σxy = 0 when there is no relationship
  9. Calculate r
  10. State the variance sum law when X and Y are not assumed to be independent
  11. Compute the variance of the sum of two variables if the variance of each and their correlation is known
  12. Compute the variance of the difference between two variables if the variance of each and their correlation is known

Chapter 14

These are the learning objectives for this portion of the class:

  1. Define linear regression
  2. Identify errors of prediction in a scatter plot with a regression line
  3. Compute the sum of squares Y
  4. Convert raw scores to deviation scores
  5. Compute predicted scores from a regression equation
  6. Partition sum of squares Y into sum of squares predicted and sum of squares error
  7. Define r2 in terms of sum of squares explained and sum of squares Y
  8. Make judgments about the size of the standard error of the estimate from a scatter plot
  9. Compute the standard error of the estimate based on errors of prediction
  10. Compute the standard error using Pearson’s correlation
  11. Estimate the standard error of the estimate based on a sample
  12. State the assumptions that inferential statistics in regression are based upon
  13. Identify heteroscedasticity in a scatter plot
  14. Compute the standard error of a slope
  15. Test a slope for significance
  16. Construct a confidence interval on a slope
  17. Test a correlation for significance
  18. State the regression equation
  19. Define “regression coefficient”
  20. Define “beta weight”
  21. Explain what R is and how it is related to r
  22. Explain why a regression weight is called a “partial slope”
  23. Explain why the sum of squares explained in a multiple regression model is usually less than the sum of the sums of squares in simple regression

Consumables

This weeks in-class presentation.

Manga Guide

  • Read: Manga Guide to Statistics sections of interest:
    • Chapter 6
    • Sadly, the Manga Guide to Statistics doesn’t cover regression specifically. However, there is a Manga Guide to Regression! Yay! It’s not available through the library. Boo.

Assignments

There are a number of assignments this week, as usual.

Week 3 Activity

This week’s activity covers correlations.

Quiz

Don’t forget about your chapter quizzes! Find them in the Quizzes menu in D2L.

Chapter 4 questions

  1. Choose a question from the end of chapter 4 in the section called “Exercises” to answer. Post the question and your answer, and make sure to justify your response.

    For example, if you determine that a type of statistic is descriptive, provide your reasoning being specific about the problem presented and your answer.

  2. Next, respond to another students’ answers by asking a question for clarification, providing a personal experience, posting a thought-provoking question, taking a controversial, but professional stand, adding something new to the conversation, quoting another student’s comment and add an additional idea based on this comment, etc.

    Your responses should be respectful and offered in a professional manner. You may wish to review the behavior Course Policies to help frame your response. Remember, you will be responding about the specific idea, issue, or question.

You may not answer a question that has been previously addressed.

Chapter 14 questions

  1. Choose a question from the end of chapter 14 in the section called “Exercises” to answer. Post the question and your answer, and make sure to justify your response.

    For example, if you determine that a type of statistic is descriptive, provide your reasoning being specific about the problem presented and your answer.

  2. Next, respond to another students’ answers by asking a question for clarification, providing a personal experience, posting a thought-provoking question, taking a controversial, but professional stand, adding something new to the conversation, quoting another student’s comment and add an additional idea based on this comment, etc.

    Your responses should be respectful and offered in a professional manner. You may wish to review the behavior Course Policies to help frame your response. Remember, you will be responding about the specific idea, issue, or question.

You may not answer a question that has been previously addressed.


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