Interpretational Issues Thus far, we compared 3 pairs of exams using 3 t-tests. A shortcoming here is that all 3 tests use the same tiny student sample. This increases the risk that at least 1 test is statistically significant just by chance. There's 2 basic solutions for this: apply a...
t.test(weight ~ group, data = my_data, paired = TRUE, alternative = "greater") Interpretation of the result Thep-valueof the test is 6.210^{-9}, which is less than the significance level alpha = 0.05. We can then reject null hypothesis and conclude that the average weight of the mic...
These results were confirmed by pairedchoice tests, where Acallepitrix sp. nov.displayed significant feeding and ovipositionpreferences for S. mauritianum and... T Olckers - 《Biocontrol》 被引量: 30发表: 2004年 Choice versus no-choice test interpretation and the role of biology and behavior in...
This article shows how to perform the paired t-test in R/Rstudio using two different ways: the R base functiont.test()and thet_test()function in the rstatix package. We also describe how to interpret and report the t-test results. References Cohen, J. 1998.Statistical ...
Step 5: Based on the the calculated t-statistic and if it falls in the rejection region or not, you determine whether you reject the null hypothesis or not Step 6: Use the conclusion of the t-test to give an interpretation in the context of the setting of the specific problem. Pair...
InterpretationThere are two types of significance to consider when interpreting the results of a paired sample t-test, statistical significance and practical significance.Statistical SignificanceThe p-value determines the Statistical significance. The p-value gives the probability of observing the test ...
Interpretation Statistical significance is determined by looking at the p-value. The p-value gives the probability of observing the test results under the null hypothesis. The lower the p-value, the lower the probability of obtaining a result like the one that was observed if the null hypothesis...
3A). Results from single-sample gene set enrichment analysis (ssGSEA) further showed that metastatic lesions had higher immune scores (median 838.6 vs 644.3, P = 0.01, paired t test, Fig. 3B), compared to paired primary lesions. But there was no significant difference between metastatic ...
If we were to report the results of this paired t test in a single sentence, we could write: “There was a higher number of cells before (10257 ± 1430 cells) than after (5239 ± 861 cells) a 6-hour treatment with drug X, t(6) = 13.55, p < 0.0001.” ...
Single-Factor Repeated-Measures Designs: Analysis and Interpretation The parametric tests that we discussed were the t test for paired or correlated samples and the single-factor repeated-measures ANOVA. We also mentioned ... JA Gliner,GA Morgan,RJ Harmon,... - 《Journal of the American ...