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Correlation and Linear Regression

Correlation and Linear Regression. Tools : S catterplot, correlation coefficient , linear regression. If two variables are somehow related, there would be some trend in the scatter plot. 1. Scatterplot. Scatterplot Q2. Scatterplot. Linearity; Direction ; Outlier.

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Correlation and Linear Regression

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  1. Correlation and Linear Regression

  2. Tools: Scatterplot, correlation coefficient, linear regression

  3. If two variables are somehow related, there would be some trend in the scatter plot. 1. Scatterplot

  4. Scatterplot Q2

  5. Scatterplot Linearity; Direction; Outlier

  6. 2. Correlation Coefficient Measure the strenght of the linear relationship of two variables. Sign: + , - Magnitude: [-1,1] Partial correlation

  7. Correlation Coefficient Q3 • Pearson correlation

  8. Partial Correlation Coefficent

  9. Regression Model Assumptions: Error follows a normal distribution with mean0 andconstant standard deviation σ.

  10. Regression Q1 e)

  11. Regression Output

  12. Q1 e) iii. Independent two-sample t test vs. t-test about the slope in regression model

  13. Regression cont. Q4

  14. Check normality? same constant standard deviation?

  15. Data  Transform data  Recode into different variables • Data  Select cases • Analyze  Descriptive  Explore (QQ Plot) • Analyze  Compare Means  Independent samples t-test (One sided!)

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