Correlations
Sponsored Links
This presentation is the property of its rightful owner.
1 / 43

Correlations PowerPoint PPT Presentation


  • 129 Views
  • Uploaded on
  • Presentation posted in: General

Correlations. 11/5/2013. BSS Career Fair. Wednesday 11/6/2013- Mabee A & B 12:30-2:30P. Readings. Chapter 8 Correlation and Linear Regression (Pollock) (pp. 182-187 ) Chapter 8 Correlation and Regression (Pollock Workbook). Homework Due 11/7. Chapter 7 Pollock Workbook Question 1

Download Presentation

Correlations

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Correlations

11/5/2013


BSS Career Fair

  • Wednesday 11/6/2013- Mabee A & B

  • 12:30-2:30P


Readings

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

  • Chapter 8 Correlation and Regression (Pollock Workbook)


Homework Due 11/7

  • 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


Opportunities to discuss course content


Office Hours For the Week

  • When

    • Wednesday10-12

    • Thursday 8-12

    • And by appointment


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.


Measures of Association


Why Hypothesis Testing

  • To determine whether a relationship exists between two variablesand did not arise by chance. (Statistical Significance)

  • To measure the strength of the relationship between an independent and a dependent variable? (association)


Measures of Association for Nominal Variables


Measures of association For Cross-Tabs

Nominal

Ordinal

Strength

Significance

Direction!

  • Strength

  • Significance


Ordinal Measures of Association


Adding a Third Variable

How to Control for a Variable?


A Third Variable

  • the relationship between two variables may be spurious, weak or even too strong

  • "controlling" for a third variable is a method of removing or separating the effects of another variable.

  • This gets at the underlying relationship


Why Add the Third Variable

  • Is there an antecedent variable at play?

  • Is the observation different for different groups of people


Marijuana and a Third Variable

  • H1: People with children will have different views on legalization than others of the same ideology

  • Cross-tabs

    • Input Row Variable

    • Input Column Variable

    • To control for a variable place it in the area that says Layer 1 of 1.


Views on Homosexuality, Party ID and Race

  • DV- homosex2

  • IV- partyid3

  • Control- race 2


Finally Correlations

You have been waiting to use this


What is correlation?

  • Any relationship between two variables

  • Correlation does not mean causation


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


Correlation Coefficients

Note the lower case r

  • Pearson’s Product Movement (Pearson’s r)

  • A way of measuring the goodness of fit between two continuous variables


Rules on Correlations

  • Variables must be continuous.

  • You cannot use ordinal or nominal variables here

  • Small samples >30 can give you odd results


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


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.


Significance and Strength

  • Significance Levels: We use the .05 level

  • Count your Stars(if available)

    • *=significant at .05

    • **= significant at.01

    • No Stars= No Significance

  • Relationship strengths of r-square values

    • .000 to .10 = none-

    • .11-.20 weak-moderate

    • .20-.35 moderate

    • .35-.50 moderate- strong

    • .50 there is a strong relationship


An Example from long ago


The Previous Example

  • We Square the correlation value .733

    • This gives us a value of .537 (r-square)

  • From this we can say 53.7% (PRE) of the variation in the dependent variable can be explained by the independent variable

  • We cannot, however, say that being Baptist increases the syphilis rate.


American Cities

  • Violent Crime Rate, Teen Unemployment Rate, Roadway congestion, Heart Disease


World Health Indicators

  • Coal consumption , Adequate Sanitation, Child Mortality, Child Immunization


Correlations in SPSS

  • Analyze

    • Correlate

    • Bivariate

  • You can include multiple variables


Scatterplots


A Way of Visualizing a Correlation


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!


CO2 and Urban Population


Scatterplots in SPSS


How to do it

  • Graphs

  • Legacy Dialogs

  • Scatter/Dot...


A Window pops up

Select simple

Choose Define


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


Including a fit Line with your Scatterplot


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)


  • Login