... - Use z-test when σ1 and σ2 are known - Use pooled-variance t test when σ1 and σ2 are unknown but equal - Use separate-variance t test when σ1 and σ2 are unknown and unequal 2. Conduct a test of hypothesis for paired or dependent observations, using the paired t-test 3. Conduct a test of hypothesis ...
Analysis of Variance: Comparing two or more means
... standard deviation for each group. o Moderate violations are also not serious. o As long as the largest group variance is no more than twice the smallest group variance, especially when sample sizes are equal across groups. o Misleading results may also occur with the F-test if the largest sample st ...
... standard deviation for each group. o Moderate violations are also not serious. o As long as the largest group variance is no more than twice the smallest group variance, especially when sample sizes are equal across groups. o Misleading results may also occur with the F-test if the largest sample st ...
ADVANCED PLACEMENT (AP) STATISTICS Grades 10, 11, 12
... Standard: Estimate population parameters and test hypotheses. I can estimate population parameters and margins of error. I can discuss the properties of point estimators, including unbiasedness and variability. I can apply and explain the properties of confidence levels and confidence interval ...
... Standard: Estimate population parameters and test hypotheses. I can estimate population parameters and margins of error. I can discuss the properties of point estimators, including unbiasedness and variability. I can apply and explain the properties of confidence levels and confidence interval ...
Unit 12-1
... Two-Sample Procedures with means • The goal of these inference procedures is to compare the responses to two treatments or to compare the characteristics of two populations. • We have INDEPENDENT samples from each treatment or population ...
... Two-Sample Procedures with means • The goal of these inference procedures is to compare the responses to two treatments or to compare the characteristics of two populations. • We have INDEPENDENT samples from each treatment or population ...
HARVARDx | HARPH525T114-G003200_TCPT
... OK, so now we're not talking central limit theorem anymore. Now we're talking about the original distribution of the data. Which in this case, because Its heights, is actually approximately numbered. If the original data were zeros and ones, like coin tosses, this wouldn't work. But for height it w ...
... OK, so now we're not talking central limit theorem anymore. Now we're talking about the original distribution of the data. Which in this case, because Its heights, is actually approximately numbered. If the original data were zeros and ones, like coin tosses, this wouldn't work. But for height it w ...
Document
... – The Type II error, β, is the probability of not rejecting the null hypothesis when the alternative hypothesis was actually true – Type II errors can be computed only when the alternative hypothesis is also an equality – The power of a test, 1 – β, measures how well the test distinguishes between t ...
... – The Type II error, β, is the probability of not rejecting the null hypothesis when the alternative hypothesis was actually true – Type II errors can be computed only when the alternative hypothesis is also an equality – The power of a test, 1 – β, measures how well the test distinguishes between t ...