World’s Best Colleges Weightings and Statistical Scores

How are the weights and statistical scores determined for U.S. News’s World's Best Colleges rankings?

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Weightings and Statistical Scores

How are the weights and statistical scores determined for U.S.News & World Report's World's Best Colleges and Universities rankings—which are based on data from THE-QS World University Rankings produced in association with QS Quacquarelli Symonds?

This page explains in detail the process (called standardization or z-score aggregation) used to convert raw scores into the final scores that appear in our World's Best Colleges rankings tables.

Designing a ranking on a single variable is relatively straightforward. Compiling a multi-index ranking is a little more complex. In combining the indexes for U.S. News's World's Best Colleges and Universities rankings, the following guiding principles have been followed:

  • Fair and even application of weighting across the whole range for each indicator
  • Intuitive and comparable scores for each of the five indicators
  • Great strengths in particular broad subject fields should contribute to the overall position of an institution

Weightings and the Statistical Calculations

The allocation of weightings for U.S. News's World's Best Colleges and Universities rankings based on data from THE-QS World University Rankings remains the responsibility of the team at Times Higher Education. The current weightings—assigned by indicator—are at this link. Once the data are collected and the weightings are decided upon, the next step is to calculate standard scores for each column of data so that they are compatible. This allows us to combine the data reliably and apply the weightings fairly in the calculation of the overall score. From 2007, a more complicated but widely used standardization or normalization method has been adopted involving z-scores. There are numerous online sources explaining how this works, including a Wikipedia entry and a UCLA article.

To prepare for the application of z-scores, a natural log is first applied to the raw data for the given indicator, be it a weighted total from the peer review or an (inverted) student faculty ratio, to draw in the outliers, and once the scores are calculated, their position on the normal curve is plotted, resulting in their score for each indicator.

Compiling the Final Scores

Compiling the final score is relatively straightforward. We simply multiply each indicator's standardized score by its weighting factor, sum each school's standardized scores together, round to one decimal place, and then scale to the top-performing institution, resulting in a final score out of 100.