Testing The Mean For Business Data:  Should One Use The Z-Test, T-Test, F-Test, The Chi-Square Test, Or The P-Value Method?

Liang, Jiajuan; Pan, William

doi:10.19030/tlc.v3i7.1704

Cited by 5 publications

(3 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The performance tests and the spatial distribution of the predicted and actual data are shown in the form of radars and scattergram graphs (Figure 9). In addition, a set of parametric and non-parametric tests, which were the T-test [33], Z-test [34], F-test [35], sign test [36], and WSRtest [37] were applied to verify if there were significant differences in the means, variance, and distribution between the real and predicted data for each model. The results showed that the best performance and distribution of predicted data compared to the actual values was obtained by the MR-CART hybrid model, with R 2 , R 2 Adj shown in the graphs equaling 0.9884 and 0.9883, respectively.…”

Section: Discussionmentioning

confidence: 99%

A Hybrid Water Balance Machine Learning Model to Estimate Inter-Annual Rainfall-Runoff

Aieb

Liotta

Kadri

et al. 2022

Sensors

View full text Add to dashboard Cite

Watershed climatic diversity poses a hard problem when it comes to finding suitable models to estimate inter-annual rainfall runoff (IARR). In this work, a hybrid model (dubbed MR-CART) is proposed, based on a combination of MR (multiple regression) and CART (classification and regression tree) machine-learning methods, applied to an IARR predicted data series obtained from a set of non-parametric and empirical water balance models in five climatic floors of northern Algeria between 1960 and 2020. A comparative analysis showed that the Yang, Sharif, and Zhang’s models were reliable for estimating input data of the hybrid model in all climatic classes. In addition, Schreiber’s model was more efficient in very humid, humid, and semi-humid areas. A set of performance and distribution statistical tests were applied to the estimated IARR data series to show the reliability and dynamicity of each model in all study areas. The results showed that our hybrid model provided the best performance and data distribution, where the R2Adj and p-values obtained in each case were between (0.793, 0.989), and (0.773, 0.939), respectively. The MR model showed good data distribution compared to the CART method, where p-values obtained by signtest and WSR test were (0.773, 0.705), and (0.326, 0.335), respectively.

show abstract

Section: Discussionmentioning

confidence: 99%

A Hybrid Water Balance Machine Learning Model to Estimate Inter-Annual Rainfall-Runoff

Aieb

Liotta

Kadri

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…The F distribution is based on a ratio of T distributions, whereas the c 2 distribution is the square of the Z distribution (which the T converges to through the central limit theorem). 26 Therefore, the authors hold that the analyses of single-item measures demonstrated here re-address central limit theorem ideology for PROs, allowing for researchers to analyze raw data scores (viewed as a monotonic transformation) instead of creating continuous linear transformations commonly employed to adjust the data to fit assumptions. 20 Alternate modeling techniques, such as the Tobit and ordinal logistic models, could also be used for these types of data; however, the authors chose to focus on methods commonly implemented in clinical trials.…”

Section: Discussionmentioning

confidence: 99%

Investigation Into the Effects of Using Normal Distribution Theory Methodology for Likert Scale Patient-Reported Outcome Data From Varying Underlying Distributions Including Floor/Ceiling Effects

et al. 2020

View full text Add to dashboard Cite

Objectives: Utilization of parametric or nonparametric methods for testing Likert scale data is often debated. This 2-part simulation study aims to investigate the sampling distribution of various Likert scale distributions (including floor/ceiling effects) and analyze the effectiveness of using parametric versus nonparametric tests with varying sample sizes.Methods: We simulated populations from parametric distributions binned into Likert scales. In study 1, replicates were sampled from each distribution with sizes ranging from 5 to 150 observations, calculating means with simulated 95% CIs at each sample size. In study 2, floor/ceiling effects were introduced such that the proportion of patients responding with the lowest rating varied from approximately 40% to 90%. Two-sample tests were then conducted for the 90% floor effect distribution against all other floor distributions to determine effectiveness of parametric versus nonparametric methods via 2-sided pooled t tests and Wilcoxon rank-sum tests. Coverage of the difference in means, realized P values, relative efficiency, measures of agreement in direction, and conclusion of tests were plotted by sample size. Results:The sampling distributions of the 1-sample means and SDs for most distributions converged quickly to Gaussian, with 95% coverage. One-and 2-sample t tests of the mean demonstrated acceptable coverage, type I error, and agreement.Conclusions: Simulations confirm that the sampling distribution of the mean rapidly approaches normality and appropriate tests provide adequate coverage and type I error. Two-sample t tests demonstrate appropriateness and increased statistical power gained by using parametric over nonparametric approaches, suggesting t tests should be implemented with few restrictions.

show abstract

“…The results showed that practically, no presence of the government in the field of e-commerce could lead to economic growth and increase the share of ecommerce tools in e-commerce. Liu (2013) 12 investigated the impact of ecommerce on productivity, using a unique panel dataset obtained from Taiwanese manufacturing firms for the period of 1999 to 2002. They found that both e-commerce capital had a positive influence on productivity.…”

Section: Research and Methodologymentioning

confidence: 99%

Analysis of E-Commerce Factors Influencing on Economic Development

Sodikova

2023

EIT

View full text Add to dashboard Cite

Today e-commerce has become an important part of daily life. Accessibility to e-commerce platforms is not a privilege but rather a necessity for most people. Thus, to grow more and earn higher profit it is highly recommended to have proper structure availability and easy accessibility of online sites, because it does not only determine profit and number of users but also the ranking and position of enterprise of the firm in overall business world. Also, in this paper I will focus about the growth and pattern of e-commerce in developing countries and its sales and impact in them, of all different types of e-commerce.

show abstract

Testing The Mean For Business Data: Should One Use The Z-Test, T-Test, F-Test, The Chi-Square Test, Or The P-Value Method?

Cited by 5 publications

References 3 publications

A Hybrid Water Balance Machine Learning Model to Estimate Inter-Annual Rainfall-Runoff

A Hybrid Water Balance Machine Learning Model to Estimate Inter-Annual Rainfall-Runoff

Investigation Into the Effects of Using Normal Distribution Theory Methodology for Likert Scale Patient-Reported Outcome Data From Varying Underlying Distributions Including Floor/Ceiling Effects

Analysis of E-Commerce Factors Influencing on Economic Development

Contact Info

Product

Resources

About