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Non-Chemical Decrease of Anthracnose Mango Fungus in Tropical Highlands
Published in Mark Anglin Harris, Confronting Global Climate Change, 2019
With a table of random numbers, the author selected an equal number of control panicles from each tree in each year. According to the null hypothesis, there were no differences among the means of the outcomes of treated panicles. He aimed to find treatment means that were significantly different from one another. Welch’s t-test, which compares the means of two populations of unequal variance, was used. The student’s t-test, which compares the means of two populations of comparable variance, was adopted for the comparison of dew collected from the upper and lower surfaces of leaves at the (P < .05) level of significance. Tukey’s HSD was used for assessing the variation in the number of days before the onset of observable anthracnose infection for four panicle treatments.
Analysis of Ancient and Modern Meditation Techniques on Human Mind and Body and Their Effectiveness in COVID-19 Pandemic
Published in Pallavi Vijay Chavan, Parikshit N Mahalle, Ramchandra Mangrulkar, Idongesit Williams, Data Science, 2022
Abhijeet Kushwah, Tirth Pandya, Prarthana Dhok, Prateek Koul, Pallavi Vijay Chavan, Shreeraj Vijayan, Vishal Shrivastava
Levene’s test conducted on the two groups (p = 0.019) suggested that there is enough evidence to say that the variances are significantly different between the groups. Thus, we moved on to conduct Welch’s T-test. Welch’s T-test conducted on the groups (statistic = 0.02, p-value = 0.98, dof = 28.49) suggested that there is sufficient evidence to conclude that the two groups are different. Thus, we can conclude that after a month of meditation, both ancient and modern meditation groups had statistically different SPANE-B scores.
Probabilistic seismic assessment of reinforced concrete bridges using simulated records
Published in Structure and Infrastructure Engineering, 2023
Volkan Ozsarac, Ricardo Monteiro, Gian Michele Calvi
Subsequently, for each bridge, a parametric method of statistical hypothesis testing, Welch’s t-test (Welch, 1938), is used to evaluate the statistical significance of differences in the two demand sets, which are assumed to follow a lognormal distribution. In general, Welch’s t-test is considered to be more reliable than a standard student's t-test since the equal variance assumption, which could be unreasonable in some cases, does not need to be made. The null hypothesis is that two samples being compared (in this case, the natural logarithm of MPDR sets obtained using simulated and real records), belong to normally distributed populations and have equal means. The test statistic is computed by Equation (18), where and are sample means, and are sample standard deviations, and and are the sample sizes, which are equal to the number of selected records:
Information Technology Work Value Differences
Published in Journal of Computer Information Systems, 2021
Katarzyna Toskin, Richard V. McCarthy
To answer the second research question (whether these preferences differ between IT professionals and other professions) we compared the mean scores of IT professionals to the mean scores reported by other professions using a Welch’s t-test to determine statistical significance. The Welch’s t-test does not rely on the equality of variances assumption and is therefore recommended when comparing means with unequal sample sizes.39Table 6 also presents the mean scores of the rewards for both groups along with t-test results. The t-tests assuming unequal variance revealed significant differences between IT and non-IT subjects in preferences for intrinsic rewards. Preferences for extrinsic, leisure and social rewards did not reveal any statistically significant differences between the two groups.
Comparison and assessment of NDVI time series for seasonal wetland classification
Published in International Journal of Digital Earth, 2018
Panpan Xu, Zhenguo Niu, Ping Tang
The confusion matrix was applied to the resulting classification maps to estimate the overall, producer’s/user’s accuracies, commission/omission rates, and Kappa coefficient. The overall and class-specific classification accuracies were compared between classification results. In order to assess the statistical differences between various classification results, a Welch t-test (Welch 1938) was performed on the overall, producer’s, and user’s accuracies of the three NTS to see if they were significantly different in identifying various wetland types. The Welch t-test is a parametric test for comparing means between two independent groups without assuming equal variances. This statistic is robust for testing the mean equality when homogeneity assumption is not satisfied (Fagerland and Sandvik 2009) and the sample sizes are relatively small (<30) (Zholud 2014; Dwivedi, Mallawaarachchi, and Alvarado 2017).