We have been accepted at the Valencia Methodology Congress in July / 2020 the following presentation in POSTER format, which we share with our followers, clients, curious ...
Title
App for Android and iOS for hypothesis testing: relationships between two variables.
Author
GASPAR BERBEL GIMÉNEZ. University School Mediterrani, UdG. Dpt. of economics, accounting and statistics ..
Collaborate: EMILI ÁLVAREZ REBOLLO. Computer consulting LEULIT, sl
Purpose
To allow a student or a researcher — in a maximum of 4 clicks — to reach the proper test of relation between two variables, showing how it is done and how the test is interpreted and finished, in APA style, with IBM-SPSS.
Method / Design
Its creation is motivated by the need to understand what is behind the systematic and the logic of parametric and non-parametric hypothesis tests, as they are currently applied.
It is part of a learning system based on the PLE (Personal Learning Environment), gathered in the statistics manual “Paola learns statistics. From a PLE ”(Berbel, 2020)
Results
Firstly, the user will be asked to indicate which are the variables that you want to relate, its typology (categorical or metrical). Once the combination is introduced, the app guides you through the application conditions (effective, normal law). When the filters are applied, the app will indicate the user the statistic test or procedure to apply to obtain the possible association between these variables. The possible tests that the app will suggest are the following ones: Chi square, t-test independent measures, t-test related measures, anova, correlation or parametrical tests. If the metrical variable does not follow the normal law - non parametrical tests - the application will suggest: U-Mann Whitney, T of Wilconox, Kruskal Wallis test, Spearman correlation.
Conclusions
The app ESTATEST allows the user to know the possible analyzes to test for hypotheses about the relationships between two variables in a simple and intuitive way. It is an excellent didactic tool for any student or researcher who must relate variables.
Keywords: Research design applications, Inferential statistics, Bivariate relationships
Link to video: https://youtu.be/TMymROdmrm4
Qualification
App to learn and test the relationship between two variables, for Android and iOS
Name (s) and affiliation (s) of the authors
GASPAR BERBEL GIMÉNEZ. Mediterrani University School, attached to the UdG. Department of economics, accounting and statistics.
Collaborator: EMILI ÁLVAREZ REBOLLO. IT consultant LEULIT, sl
Purpose
Allow a student or researcher, in a maximum of 4 clicks, to arrive at the appropriate test of the relationship between two variables, showing how the test is performed and how it is interpreted-concluded, in APA style, with SPSS.
Method / Design
Its elaboration starts from the need to understand the systematics and logic behind parametric and non-parametric relationship tests. Within hypothesis tests, as currently applied. It is part of a learning system based on the PLE (Personal Learning Environment), collected in the statistics manual “Paola learns statistics. From a PLE ”(Berbel, 2020).
Results
First, it will ask you to mark the variables that you intend to relate, their typology (categorical or metric), once the combination has been entered, the app guides you through the conditions of application (effective, normal law). Applied the filters the app It will indicate the test or statistical procedure to be applied to see the possible association between the variables. The tests that will be proposed when the application conditions are met are: Chi square, independent measured t-tests, related measures t-tests, anova, correlation… parametric tests. When the metric variable does not follow the normal law - nonparametric tests - the app will propose: U of Mann Whitney, T of Wilcoxon, kruskal Wallis test, Spearman correlation.
Conclusions
The app ESTATEST allows in a very simple and intuitive way to know the possible relationship tests between any two variables. Excellent teaching tool for any student or researcher who must relate variables.
Video link: https://youtu.be/TMymROdmrm4
