QSO 510 Discussion 5 - deviation is known to be = 0.3 cm A...

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Z-scores are a conversion of individual scores into a standard form. The conversion is based on your knowledge about the population’s standard deviation and mean. A z-score tells you how many standard deviations from the mean your result is. Like z-scores, t-scores are also a conversion of individual scores into a standard form. However, t-scores are used when the conversion is made without knowledge of the population standard deviation and mean. Seeing as you don’t know those parameters for your population, you make an estimate by using the statistics from your sample (Statistics How To, 2015). An example of a z confidence: A manufacturer produces bolts with a nominal length of 15 cm. The actual lengths vary slightly. The process is stable and the population standard
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Unformatted text preview: deviation is known to be = 0.3 cm. A sample of 50 bolts has a mean length of = 14.85 cm. In this case = 0.3, n = 50, = 14.85. The approach is to find a confidence interval of 95% is given by: 14.85 ± 1.96 × i.e. (14.77, 14.93) cm Interpretation - with 95% confidence the interval (14.77, 14.93) contains the population mean µ of all bolts produced by the process. The interval does not contain 15.0cm. The manager at that time may determine that the production machinery be recalibrated to get the bolt lengths closer to 15 cm. N/A. (2015). T-Score vs. Z-Score: What’s the Difference? Statistics How To. Retrieved 1/19/2016. http://www.statisticshowto.com/when-to-use-a-t-score-vs-z-score/...
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