Part 2. Power calculations continued common scenario for questions: The investigators plan to use a sample...

 

 

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Part 2. Power calculations continued common scenario for questions: The investigators plan to use a sample of size 60 to carry out tests of hypotheses with the null hypothesis = 250. They think the population standard deviation is equal to 50. They really want their hypothesis tests to correctly reject the null hypothesis if = 235. Use R pwr.t.test from the pwr package or similar functions. 1. (1 point) If the investigators use a = .05 and a one-sided alternative hypothesis < 250, Show how you found the answer. what is the power of the test? 235-250=-15/50= -3/10 >pwr.t.test(type = "one.sample",d = -3/10, n = c(60), alternative = "less", sig.level = .05) One-sample t test power calculation n = 60 d = -0.3 sig.level = 0.05 power = 0.7428494 alternative = less 2. (1 point) If the investigators use a = .05 and a two-sided alternative hypothesis #250, Show how you found the answer. what is the power of the test? >pwr.t.test(type = "one.sample",d = -0.3, n = c(60), alternative = "two.sided", sig.level = .05) One-sample t test power calculation n = 60 d = 0.3 sig.level=0.05 power = 0.6277528 alternative = two.sided 3. (1 point) Compare your answers from Q1 and 2. Is there a difference in achieved power when using a one sided vs. two-sided hypothesis test? Part 2. Power calculations continued common scenario for questions: The investigators plan to use a sample of size 60 to carry out tests of hypotheses with the null hypothesis = 250. They think the population standard deviation is equal to 50. They really want their hypothesis tests to correctly reject the null hypothesis if = 235. Use R pwr.t.test from the pwr package or similar functions. 1. (1 point) If the investigators use a = .05 and a one-sided alternative hypothesis < 250, Show how you found the answer. what is the power of the test? 235-250=-15/50= -3/10 >pwr.t.test(type = "one.sample",d = -3/10, n = c(60), alternative = "less", sig.level = .05) One-sample t test power calculation n = 60 d = -0.3 sig.level = 0.05 power = 0.7428494 alternative = less 2. (1 point) If the investigators use a = .05 and a two-sided alternative hypothesis #250, Show how you found the answer. what is the power of the test? >pwr.t.test(type = "one.sample",d = -0.3, n = c(60), alternative = "two.sided", sig.level = .05) One-sample t test power calculation n = 60 d = 0.3 sig.level=0.05 power = 0.6277528 alternative = two.sided 3. (1 point) Compare your answers from Q1 and 2. Is there a difference in achieved power when using a one sided vs. two-sided hypothesis test?