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Hypothesis Testing: The Ultimate Beginner's Guide to Statistical Significance
- Narrado por: Tim Carper
- Duración: 1 h y 54 m
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Hypothesis Testing: The Ultimate Beginner's Guide to Statistical Significance
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Resumen del Editor
The perfect book for beginners wanting to learn about hypothesis testing & statistical significance!
Best-selling IT & mathematics author Arthur Taff presents a leading book for beginners to learn and understand hypothesis testing - specifically statistical significance. Statistical significance is a way of determining if an outcome occurred by random chance, or if something caused that outcome to be different than the expected baseline. Statistical significance calculations find their way into scientific and engineering tests of all kinds, from medical tests with a control group and a testing group, to the analysis of how strong a newly made batch of parts is. Those same calculations are also used in investment decisions.
In this book, you will get: A breakdown of all the major types of statistical significance calculations, and workings through an example using them, with an explanation of when you would use that specific type instead of one of the others. The book features an easy-to-understand approach that doesn't assume you have prior in-depth knowledge of statistics or that you regularly use an advanced statistics software package. Arthur's personal email address is included for unlimited customer support if you have any questions.
If you are a person who learns by example, then this book is perfect for you! It is a very important topic with use in a wide range of industries and situations - so dive in to get a deep understanding!
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Lo que los oyentes dicen sobre Hypothesis Testing: The Ultimate Beginner's Guide to Statistical Significance
Calificaciones medias de los clientesReseñas - Selecciona las pestañas a continuación para cambiar el origen de las reseñas.
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Total4 out of 5 stars
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Ejecución4 out of 5 stars
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Historia3 out of 5 stars
- I buy too much!
- 11-06-22
Okay... just okay
Mostly pretty good. Some logical inconsistencies. For example, null hypotheses are retained or rejected, not "accepted". You don't accept something that is already assumed by the world to be true. The novice might have to give this a couple listens to grasp the content. It does lay an okay job of laying down a logical track for understanding statistics.
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