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Correlations

Correlations. 11/7/2013. Readings. Chapter 8 Correlation and Linear Regression (Pollock) (pp. 182-187 ) Chapter 8 Correlation and Regression (Pollock Workbook). Homework Due Today. Chapter 7 Pollock Workbook Question 1 A, B, C, D, E, F   Question 2 A, B, C, D 

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Correlations

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  1. Correlations 11/7/2013

  2. Readings • Chapter 8 Correlation and Linear Regression (Pollock) (pp. 182-187) • Chapter 8 Correlation and Regression (Pollock Workbook)

  3. Homework Due Today • Chapter 7 Pollock Workbook • Question 1 • A, B, C, D, E, F   • Question 2 • A, B, C, D  • Question 3 (use the dataset from the homework page) • A, B, C, D • Question 5 • A, B, C D, E

  4. Opportunities to discuss course content

  5. Office Hours For the Week • When • Friday 10-12 • Monday 10-12 • Tuesday 8-12 • And by appointment

  6. Course Learning Objectives • Students will be able to interpret and explain empirical data. • Students will achieve competency in conducting statistical data analysis using the SPSS software program.

  7. Correlations

  8. What is correlation? • Any relationship between two variables • Correlation does not mean causation

  9. What Could Be Happening? • Variable A influences variable B • Variable B influences variable A • It is a coincidence • Some other variable (C) influences both A and B

  10. Measuring Pearson’s r • Measure from -1 to 0 to 1. • -1 means a perfect negative relationship • 0 is the absence of any relationship • +1 is a perfect positive relationship • Like Somers’ D, Pearson's "r" scores tell us • Direction • Strength of Association • Statistical significance of the measure

  11. PEARSON'S r's are PRE Measures! • Squaring the (r) value provides a measure of how much better we can do in predicting the value of the d.vby knowing the independent variable. • We call this a r2(r-square) value.

  12. Scatterplots

  13. A Way of Visualizing a Correlation

  14. More on Scatterplots • We can think of this line as a prediction line. • The closer the dots to the line, the stronger the relationship, the further the dots the weaker the line. • If all the data points are right on the regression line, then there is a perfect linear relationship between the two variables. • This only graphs a correlation...... this means that it does not mean causality nor should it be used for testing!

  15. CO2 and Urban Population

  16. Scatterplots in SPSS

  17. How to do it • Graphs • Legacy Dialogs • Scatter/Dot...

  18. A Window pops up Select simple Choose Define

  19. Adding Case Labels • put your variable in the Label Cases by area • Click on Options, and this will open up a window • Click on display chart with case labels and continue • Click OK

  20. Including a fit Line with your Scatterplot

  21. Do not use scatterplots for testing! There are better measures, especially if you have more than 1 iv. (your paper should not include any scatterplots)

  22. Lets try an example • Use the following data set • D.V. Obama • I.V. Unemp • Follow the directions from last class

  23. What is Going on? • The Line of Best Fit- • How much error is in our line. • A predictor for future values • Eyeballing the data, a state with 4% unemployment should give Obama how much support?

  24. Data

  25. Primary data • Collection • Advantages • Disadvantages

  26. Secondary Data • Collection • Advantages • Disadvantages

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