Posts by Mark Dwyer, PhD

Optimal Investment in Data Error Assessment

Assessing Data Errors is Necessary, But at What Cost?

My last post discussed some of the ways that data errors weaken the reliability of conclusions drawn from those noisy data. Even measures of the uncertainty in conclusions (such as statistical confidence intervals) can be inaccurate. This raises the question as to how one assesses data for such errors, and at what cost? The Data…

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Beware the Two-Step Process of Measuring Pay Disparities

Beware the Two-Step Process of Measuring Pay Disparities

Companies should be wary of any pay equity analysis that offers to look at wage disparities after controlling for legitimate business factors. The term “after” is open to interpretation, but a defensible, reliable pay equity assessment must measure wage disparities in a full model — one that also measures the effects of legitimate business factors…

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Clean Data Essential for Reliable Data Analysis

Clean Data Essential for Reliable Data Analysis

How much confidence can you place in the conclusions of your data analysis? For regulatory compliance actions, the cost of errors can involve fines, lawsuits, and damage to the brand. When being wrong involves significant costs, it is important to consider ways in which errors in the underlying data could be undermining your results. Many…

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Data: The Good, The Bad, and The Ugly

Data: The Good, The Bad, and The Ugly

Data analysis informs our daily business decisions, but that analysis is only as good as the data supporting it. Organizations should invest in ensuring that their decision-making is based on accurate information. As data analysis is becoming increasingly sophisticated, machine learning is becoming a sought after technology. Organizations that haven’t already incorporated machine learning predictions…

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