When states are matched on their turnout levels in 19, a paired samples T Test shows that the changes from one year to the next were small, but systematic. Paired Samples Test: % turnout in 1980 election - % turnout in 1984 electionĩ5% Confidence Interval of the Difference In fact, because the states are matched on repeated measures, we must use the Paired Samples T-Test in SPSS, which produces this very different result: Paired Samples Statistics Perhaps this systematic change is lost by only calculating the means for each year. Suppose that most states tended to demonstrate a slightly lower voting turnout rate between 19-perhaps dropping by about one point. 05 level, so it suggests that the observed difference in states' voting turnout between 19 is unlikely to have occurred by chance.īut suppose that some systematic process was going on. JMP Introductory Lab Activities Activity 13. A test statistic this small falls far short of significance at the customary. View Lab Report - 13-Hypothesis-Test-Two-Sample-t-Test1.pdf from SCMS 350 at University of Nebraska, Lincoln. Treating the 51 states as 'Independent' in computing the T-Test produces a test statistic ( t) less than one. Let's compute the T-Test for Independent Samples: Perhaps we could do a standard T-Test to check this out. Others say that the observed differene between means of only 1.1% points (55.7-54.6) could have been attributable to chance. Description: There are three distinct tests supported by this command. Both one-tailed and two-tailed tests are supported. Some say that turnout dropped because there was no third party candidate. Perform either a one sample t -test, an unpaired two sample t -test, or a paired two sample t -test. The mean voting turnout in 1984-when calculated across all the states-dropped compared with 1980. Reagan was elected in 1980 and ran for re-election in 1984 against Walter Mondale, but there was no third party candidate in 1984. The 1980 election, between incumbent president Jimmy Carter and challenger Ronald Reagan also had a third candidate, John Anderson-who had been a Republican party leader but who ran as an Independent. % turnout in presidential elections by statesĭifferent stories could be told for each of these elections, but let's concentrate on the turnout data for 19. In this instance, the standard T-Test for Independent Samples does not apply.Ĭonsider the situation of voting turnout in American states in elections since 1980. These groups are independent in the sense that cases in one group are not matched with cases in the other group.īut occasionally, researchers will want to determine whether there is a significant change in the scores of the same cases on the same variables over time. Usually, social researchers use the T-Test to test for significant differences between means observed for two independent groups, such as Democrats v. It also provides a useful resource for teachers of statistics particularly in the area of engineering.Example of paired T-Test Path: /c10 > Syllabus > Topicsand Readings > RelatingNominal and Inerval Variables > PairedT-Test Masters and advanced students in applied statistics, industrial engineering, business engineering, civil engineering and bio-science engineering will find this book beneficial. Course materials and tutorials for teaching are available on the book's companion website.Promotes the use of graphs and confidence intervals in addition to p-values.

Discusses the power of various statistical tests, along with examples in JMP to enable in-sight into this difficult topic.Pays attention to the usual parametric hypothesis tests as well as to non-parametric tests (including the calculation of exact p-values).Provides a comprehensive and rigorous presentation of introductory statistics that has been extensively classroom tested.The authors approach combines mathematical depth with numerous examples and demonstrations using the JMP software. This book provides a first course on parameter estimation (point estimates and confidence interval estimates), hypothesis testing, ANOVA and simple linear regression. Peter Goos, University of Leuven and University of Antwerp, Belgiumĭavid Meintrup, University of Applied Sciences Ingolstadt, GermanyĪ first course on basic statistical methodology using JMP Statistics with JMP: Hypothesis Tests, ANOVA and Regression

Paired t test jmp