The main assessment in this class is to reproduce an advanced analysis from a published journal article. Your job is to find an article which has also published the data (or made the data available somewhere) and recreate the analysis from scratch. You will need to keep a log of all the adjustments, detours, violations of assumptions, transformations, and anything else that you have done to arrive at your final analysis. If you cannot find an article with data published, ask your supervisor for some of his or her data from an article that is published. Anyone who still can’t find something can ask me for data.
Using one of the below techniques.
| Week | Topic | Description | Chapter |
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Introduction |
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| 1 | Background Noise | Checking that everyone has the basic knowledge required to succeed in this class.
Number Theory, t – tests, F – tests, chi square tests, Z – tests, distributions, hypothesis creation and testing. |
Ch 1 & 2 |
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Collecting Data |
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| 2 | Experimental Design | Basic Design Principles, Factorial Designs, Aliasing, Resolution | |
| 3 | Advanced Designs | Nesting, balanced vs unbalanced. | |
| 4 | Meta Analysis | Data requirements, analysis techniques, outcomes and observations | |
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Exploring Data |
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| 5 | Factor Analysis | What does it do? How does it work? When to use it? Diagnostics. | Ch 3 |
| 6 | Mapping Techniques | Multidimensional Scaling and Correspondence Analysis. How they work, when to use each one, how to interpret maps, problems and shortcomings. | Ch 10 |
| 7 | Classification Techniques | Cluster Analysis and Discriminant Analysis. What’s the difference? How do they work? When do you use each one? | Ch 7, 9 |
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Analysing Data – General Linear Model |
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| 8 | Multiple Regression | Assumptions, Residuals, Goodness of Fit, Lack of Fit, Multicollinearity, Covariates | Ch 4 |
| 9 | MANOVA | What is MANOVA? How do we interpret the results? What does it mean and why is it different from ANOVA? | Ch 8 |
| 10 | Logistic and Multinomial Logit Regression | Nominal Dependent Variables – Choices, Survival, Contagion, and other classes of dependent variables. | Ch 7 |
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Torturing Data Until They Confess |
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| 11 | Multi-Level Models | What they do, how they work, when to use them, and when to avoid them. | |
| 12 | Structural Models | The basics of Structural Equation Modelling with AMOS, or how to add 6 months to your PhD | Ch 11 |
ScholarMatic: Explanation & Answer
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