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Review A. Field's Chapter 6: "The Beast of Bias" Task 1. Complete the following table below for the remaining biases listed. An example is provided for "Outliers". Feel free to expand on the example I have provided if adding more detail would help. No. Source of Bias Definition Graphical Using Numbers to Review Why does it matter? Strategies to address: Methods of Review 1 Outliers An outlier is Histograms ; Convert data to z-scores Outliers bias parameter (1) Check whether the a score very Boxplots' estimates, They have a outliers are the result of different 2Refer to Jane Superbrain 6.4: greater impact on the data entry errors. If so, from the rest Refer to 6.9 z-scores express scores in error associated with replace the error with of the data Spotting Outliers: terms of a distribution with a that estimate. If the correct value. Easily spotted in mean of 0 and a standard sum of squared errors situations where deviation of 1; in a normal is biased, the (2) Consider whether the outliers are distribution we'd expect about associated standard outlier is due to isolated, extreme 5% to be greater than 1.96 (we error; confidence measurement errors (e.g., cases often use 2 for convenience), interval and test out-of-range values). 1% to have absolute values statistic will be biased greater than 2.58, and none to too (3) After review, you be greater than about 3.29 note that the outlier is neither the result of a data entry error or measurement error, it is most likely a genuinely unusual data point. Run the analysis with and without the outlier and note for differences in results. 2 Additivety & Linearity 3 Normally Distributed or other