A two-tailed chi-square test was used to compare the differences in requested shifts in the two patient groups. The study population consisted of 56 patients (31 short and 25 extended cradle) representing 92 treatment sites. A total of 782 port films representing 450 treatment setups were ...
Hypothesis Testing for a Difference Between Two Proportions 10:09 6:37 Next Lesson Chi-Square Test | Definition, Purpose & Examples ANOVA Test Definition, Purpose & Examples 6:47 Using ANOVA to Analyze Variances Between Multiple Groups 9:14 Ch 11. Studying for Statistics 101Hypothesis...
Thechi-square testshould be used to compare the variance (or standard deviation) of one sample against an assumed population variance (or standard deviation). Examples > withStatistics: Specify the data sample. > X≔Array9,10,8,4,8,3,0&co...
Changes in demographical characteristics between the two time periods were analyzed using the chi-square test for the categorical variables and the independentt-test or Mann–Whitney for the continuous variables. Logistic regression was used to analyze the association between BMI at the time of diagnos...
with some test statistics. For example,t-tests calculate t-values.F-tests, such as ANOVA, generate F-values. Thechi-square test of independenceand some distribution tests produce chi-square values. All of these values are test statistics. For more information, read my post aboutTest Statistics...
c) One-tailed test, N = 41, p = .01. Find the critical chi-square values for 21 degrees of freedom when alpha = 0.05 and a two-tailed test is conducted. Calculate the critical t and df. Data: Two-tailed test, N = 47, p = .05. Calculate the...
One-tailed and two-tailed tests.A one-tailed and a two-tailed test are two different techniques to compute the statistical significance of a parameter inferred from a data set, in terms of a test statistic, in statistical significance testi...
Categorical variable was showed as absolute number (percentage) and examined using chi-square test. Lacking values were imputed using multiple imputations. Statistical significance was recognized when two-tailed P < 0.05. For logistic analyses, univariate and multivariate models were set to assess...
Test Statistic Dmax = 0.4 (The maximum vertical distance between two CDFs.) P(>= Dmax) = 0.081519 (with Smirnov approximation, 1948) P(> Dmax) = 0.081524 (with Chi-square approximation) Fail to reject the null hypothesis at the 0.05 significance level. ...
most appropriate significance tests for most A/B testing data (difference between proportions), but what is said is also true for t-tests. Part of the discussion should be taken with caution with regards to tests with non-symmetric distributions, such as F-tests, Chi square tests, and ...