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...
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...
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...
We’ll use the pipe-friendlyt_test()function [rstatix package], a wrapper around the R base functiont.test(). The results can be easily added to a plot using theggpubrR package. stat.test <- mice2.long %>% t_test(weight ~ group, paired =TRUE) %>% add_signific...
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...
Step 6: Use the conclusion of the t-test to give an interpretation in the context of the setting of the specific problem. Paired t test example Question: Assume that you have the following sample of paired data. Sample 1 Sample 2 Difference = Sample 1 - Sample 2 4 2 2 5 3 2 6 ...
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 ...
Interpretation By looking at the ‘Significantly different? (P<0.05)’ output, a ‘Yes’ is given which essentially means that our results are significantly different from each other. The exact p value is given next to ‘P value’. In this case a p value of < 0.0001 indicates a very sig...
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 ...