Small Sample From Normal Distribution

Small Sample From Normal Distribution - # of Success = 78 ....

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R Input x = c( 25.8, 36.6, 26.3, 21.8, 27.2) t.test( x, alternative="greater", mu=25 , conf.level=.95 ) R Output One Sample t-test data: x t = 1.0382, df = 4, p-value = 0.1789 alternative hypothesis: true mean is greater than 25 95 percent confidence interval: 22.32433 Inf sample estimates: mean of x 27.54 Significance level .05 Critical value qt(1-.05,df=4) > 2.131847
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Binomial Example
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Unformatted text preview: # of Success = 78 . N = 100 Ho: p=.6 Ha: p > .6 binom.test(78, 100, p=.6, alternative = "greater", conf.level= .95) Exact binomial test data: 78 and 100 number of successes = 78, number of trials = 100, p-value = 0.0001072 alternative hypothesis: true probability of success is greater than 0.6 95 percent confidence interval: 0.7009882 1.0000000 sample estimates: probability of success 0.78...
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Small Sample From Normal Distribution - # of Success = 78 ....

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