Linear & Logistic Regression

Predictive Analytics
  • 10 Videos | 45m 50s
  • Includes Assessment
  • Earns a Badge
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Regression modeling investigates relationships between dependent and independent variables and is heavily relied upon for predictive analytics and data mining applications. Explore both the linear and logistic regression models.

WHAT YOU WILL LEARN

  • recognize characteristics of linear regression
    calculate sum of squared errors
    determine the OLS parameters
    make regression inferences
    list key features of logistic regression
  • recognize the logit transformation and likelihood functions
    interpret logistic regression results
    calculate the odds ratio
    recognize key considerations for logistic regression
    determine and interpret the statistical significance of individual variables and of the overall model

IN THIS COURSE

  • Playable
    1. 
    Linear Regression Overview
    5m 18s
    UP NEXT
  • Playable
    2. 
    Sum of Squared Errors
    3m 41s
  • Locked
    3. 
    Ordinary Least Squares (OLS)
    2m 59s
  • Locked
    4. 
    Drawing Inferences
    4m 23s
  • Locked
    5. 
    Logistic Regression Overview
    4m 27s
  • Locked
    6. 
    Logit Transformation and the Likelihood Function
    6m 33s
  • Locked
    7. 
    Interpreting Results and Testing Significance
    3m 39s
  • Locked
    8. 
    Odds Ratio and Relative Risk
    3m 42s
  • Locked
    9. 
    Considerations for Logistic Regression
    2m 55s
  • Locked
    10. 
    Exercise: Linear Regression Statistical Inference
    3m 44s

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