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The following was a clip from a recent presentation, where I discuss how hypothesis testing can help you draw more statistically valid conclusions from data, and avoid misleading or incorrect conclusions.
I share two examples. The first was a data set from the Denver Sheriff's Department, where they graphed and analyzed intake use of force incidents, but their conclusions don't seem to match the graphic.
The 2nd example was data I pulled for a nonprofit I ran that showed the day of the week and time of day had no impact on click through rates on our monthly email newsletter.
Learn more about BPI
Have a question? Submit a voice message at Podcasters.Spotify.com
By Brion Hurley4.5
88 ratings
The following was a clip from a recent presentation, where I discuss how hypothesis testing can help you draw more statistically valid conclusions from data, and avoid misleading or incorrect conclusions.
I share two examples. The first was a data set from the Denver Sheriff's Department, where they graphed and analyzed intake use of force incidents, but their conclusions don't seem to match the graphic.
The 2nd example was data I pulled for a nonprofit I ran that showed the day of the week and time of day had no impact on click through rates on our monthly email newsletter.
Learn more about BPI
Have a question? Submit a voice message at Podcasters.Spotify.com

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