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Interactive video lesson plan for: Z-Score in Statistics, for pitchers Kershaw and Martinez, on StatsCenter (Ep. 14)

Activity overview:

How can we compare the ERA’s of Clayton Kershaw vs. Pedro Martinez, if they pitched in different baseball eras? Simple: calculate their z-scores! Using each pitcher’s population mean and standard deviation, we can make a direct comparison of how well each of them did, relative to his particular competition. Since we’re in the field of statistics dreams, we’ll also need to discuss their percentiles within the Empirical Rule as well, so we call upon immaculately dressed in-field reporter Jordan Cohen to uncurve this concept.

StatsCenter is presented by:

The Michelson 20MM Foundation – a Los Angeles based non-profit organization founded and funded by Dr. Gary. K Michelson, investing in innovative technology solutions and entrepreneurs to improve student opportunities and educational outcomes. For more information on Gary K. Michelson and the organization please visit
http://20mm.org.

Jordan Cohen, Executive Producer -- a rising senior at Brentwood High School dedicated to helping more students access life-changing educational opportunities.

YayMath.org – A free online collection of fun and connectable math video lessons, filmed LIVE in the classroom, and now in studio! See what inspired education looks like, at
http://YayMath.org

Contact Light Films – Sparking conversations on issues that matter, revealing evocative, thought-provoking stories that drive action, and bringing relevant causes and movements to the forefront. For more, please visit
http://contactlightfilms.com

Tagged under: Z-score,Clayton Kershaw,Pedro Martinez,Empirical Rule,ERA,standard deviation,interquartile range,IQR,outliers,normal distribution,normal curve,bell curve,baseball,pitching,steroids,68-95-99.7,Rule Thumb,Dodgers,sigma,Red Sox,statistics,AP statistics,stats,SAT,ACT,GRE,GMAT,math learning videos,StatsCenter,SportsCenter,The Michelson 20MM Foundation,Jordan Cohen,Gary K. Michelson,Contact Light Films

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Estimating Areas Under the Normal Curve Using Z-Scores

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