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Text Box:   Social Science Statistics Modeule 2: Regression Diagnostics in SPSS

 

 

Lecture Slides

Lab Notes

Assignment

Further Resources

Text Box:   Lecture Slides 

 

 


SSS2 Introduction

 

SSSII Lecture 1: Correlation and Regression 

    1. Covariance & Correlation Coefficients
    2. Multiple Regression
    3. Interpreting Coefficients
    4. Inference
    5. Coefficient of Determination

SSSII Lecture 2: Prediction and ANOVA

    1. Prediction
    2. ANOVA in regression
    3. F-Test
    4. Regression assumptions
    5. Properties of OLS estimates

SSSII Lecture 3: Non-Linearities

    1. Consequences of non-linearities
    2. Testing for non-linearities
         (a) visual inspection of plots
         (b) t-statistics
         (c) structural break tests
    3. Solutions
         (a) transform variables
         (b) split the sample
         (c) dummies
         (d) use non-linear estimation techniques

SSSII Lecture 4: F-Tests

    1. General Test for a set of linear restrictions
    2. Testing homogenous restrictions
    3. Testing for a relationship
    4. Testing for Structural Breaks
    Excel Template for F-Tests

SSSII Lecture 5: Ommitted Variables & Measurement Errors

    1. Regression Assumptions
    2. Omitted Variables
    3. Irrelevant Variables
    4. Errors in Variables
    5. Error Term with zero mean

SSSII Lecture 6: Heteroscedasticity

    1. What is heteroscedasticity?
    2. Causes
    3. Consequences
    4. Detection
    5. Solutions

SSSII Lecture 7: Multicolinearity & Modeling Strategies

    1. What is multicolinearity?
    2. Causes
(dummy variable trap, linear sums, same effects)
    3. Consequences (increased SEs, unstable coefficients, wrong signs)
    4. Detection
(instability, t-ratios, VIF, Condition Indices)
    5. Solutions
(do nothing, drop variables, factor analysis)
    6. Modelling Strategies
(General to Specific; Specific to General)


SSSII Lecture 8:  Binary Dependent Variable Estimation

1.      Overview of Non-Continuous Dependent Variables

2.      Linear Probability Model

3.      Logit

4.      Logit Estimation & Interpretation

5.      Multiple Logit Regression

6.      Using Odds Ratios   

SSSII: Lecture 9: Revision Lecture

 

 

Text Box:   Lecture notes & Lab Exercises for SSS2: 


  • Introduction: Why study regression? Click here. (Revised 17th Jan 2011)
  • Ch1: Correlation and Inference. Click here. (Revised 17th Jan 2011)
  • Ch1: Answers and Syntax (Revised 17th Jan 2011)
  • Ch2: Prediction and ANOVA (Revised 31st Jan 2011). Click here.
  • Ch2: Answers (Revised 31st Jan 2011). Click here.
  • Ch3: Non-Linearity (Revised 11th Feb 2011). Click here.
  • Ch3: Answers (Revised 11th Feb 2011). Click here.
  • Ch4: F-tests (Revised 21st Feb 2011). Click here.
  • Ch4: Answers (Revised 21st Feb 2011). Click here.
  • Ch4: Ftests Excel template (Revised 21st Feb 2011). Click here.
  • Ch5: Ommitted Variables. Click here.
  • Ch5: Answers. Click here.
  • Ch6: Heteroscedasticity. Click here.
  • Ch6: Answers. Click here.
  • Ch7: Multicolinearity. Click here.
  • Ch7: Answers. Click here.
  • Ch8: Logit. Click here.

Text Box:   SSS2 Assignment 2011: 



Please note your final assignment for SSS2 is due for submission Thursday 14th April 2011.
When submitting your assignment please supply the following:

·        2 copies of the assignment, both including standard cover page

·        1 completed and signed declaration of originality form

Assignments must be deposited in the mailbox outside the College Office, now located in room 107 of Florentine House, 53 Hillhead Street (next to the Library and Fraser Building).

Any assignments failing to meet the above conditions will not be marked until the submission is completed and may be subject to a marking penalty.

Details of the assignment, data and other resources are available below: 

·        Assignment: data and brief.

·        SNS website

·        Equality Trust

·        Professors Richard Wilkinson & Kate Pickett respond to critics.

 

Text Box:   SSS2 Further Resources: 


Data for SSSII:

SSSII Lecture Slides from 2006/2007:

  • To download Lecture 1 click here.
  • To download Lecture 2 click here.
  • To download Lecture 3 click here.
  • To download Lecture 4 click here.
  • To download Lecture 5 click here.
  • To download Lecture 6 click here.
  • To download Lecture 7 click here.
  • To download Lecture 8 click here.
  • To download Lecture 9 click here.

Click here for a copy of the 2007 assignment brief. Click on the link below to download the mortality dataset:

Macro for computing White's Standard Errors:

The following macro was written by Andrew F. Hayes of Ohio State University.  See hcreg.pdf for technical background to the macro. To use the macro, follow the steps below:

1. Copy both of the following files onto your hard disk. 

2. Then open whitesSE.sps file (tells you how to use the hcreg file).