Hypothesis Tests and Exploratory Analysis Using R Commander and Factoshiny

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Here, students determine the total protein content in whey protein samples using the Lowry assay. Quantitative analysis was carried out using absorbance measured at 750 nm (standard method) and 96-well-plate digital images obtained using smartphones (proposed method). The proposed method was carried out using two smartphones (1 and 2). Smartphone 1 had a higher resolution than smartphone 2. The statistical evaluation of the data set produced by the students was carried out using JASP (Jeffreys's Amazing Statistics Program), and it was a valuable tool to teach descriptive statistics and hypothesis tests. We chose JASP because it is free and open-source software with a graphical user interface. The protein percentage found in five whey protein samples using the standard method during three lab classes was compared using one-way and two-way ANOVA. Five whey protein samples were analyzed using the standard method and the proposed methods (smartphones 1 and 2). The results were compared using one-way repeated measure ANOVA (RMANOVA) and mixed-factor ANOVA. During the statistical analysis of the data set, students identified outlier results using boxplots and checked data normality using the Shapiro−Wilk test, histograms, and boxplots. They learned the difference between dependent and independent variables and compared variances using Levene's test (dependent variables) and Mauchly's test (independent variables). The interpretation of statistical tests was also carried out using descriptives plots, boxplots, and raincloud plots.

Section: Methodsmentioning

confidence: 99%

Whey Protein Analysis Using the Lowry Assay and 96-Well-Plate Digital Images Acquired Using Smartphones

Assink Junior,

de Jesus,

Borges

2023

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“…The students that did this experiment had no previous experience in statistical calculation, but they were introduced to boxplots using the periodic table properties. 12 The JASP does hypothesis tests in a click-and-go manner. It did several plots, such as boxplots, rainclouds, and discriminant plots, which provide an interpretation beyond the p-value interpretation.…”

Section: ■ Experimental Overviewmentioning

confidence: 99%

“…Looking for a GUI and free software, statistical calculations were conducted using R Commander. , However, it does not provide high-resolution figures and tables that can be easily exported. For these reasons, statistical calculations were conducted using Jeffreys’s Amazing Statistics Program (JASP). , It is written in the R programming language and released under a free- and open-source license.…”

Section: Introductionmentioning

confidence: 99%

Teaching Descriptive Statistics and Hypothesis Tests Measuring Water Density

Silva de Souza,

Borges

2023

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This laboratory experiment was divided into four parts. In the first part, students evaluate previously published data and check their normality using histograms, Q−Q plots, the Shapiro−Wilk test, and boxplots. In the second part, two different groups were compared. First, data normality and homoskedasticity were checked by using the Shapiro−Wilk test and Levene's test, respectively. Then the group mean was compared using the Student, Welch, and Mann−Whitney tests. In the third part, the famous Iris flower data set was analyzed, where data normality and homoskedasticity were checked. Then, three independent groups were compared using ANOVA, without correction, and using the Welch and Brown-Forsythe corrections. The Iris flowers data set was also compared using the nonparametric version of ANOVA (Kruskal−Wallis test) and post hoc tests such as the Tukey test (parametric) and Dunn's test (nonparametric). In the fourth part, students measured the density of water using four pieces of glassware (a beaker, a graduated cylinder, a volumetric pipet, and a graduated pipet). After the experiment, the data' normality and homoskedasticity were checked. Then, the data was compared using ANOVA and post hoc tests. The results of these tests were visually interpreted using raincloud and discriminant plots. These data provide a starting point for teaching precision, accuracy, descriptive statistics, and hypothesis tests. Statistical analysis was carried out using Jeffreys's Amazing Statistics Program (JASP), which is free and open-source software that provides several graphical interpretations of the hypothesis test.

“…In recent years, programming software such as MATLAB, − Python, − Octave, − R Project, and R Commander have been used to teach statistical calculations. Here, boxplots were built using Jeffreys’s Amazing Statistics Program (JASP) .…”

Section: Introductionmentioning

confidence: 99%

“…Data sets can be compared, represented, and visualized using boxplots. − Thus, in this activity, the chemical and physical properties of elements (metals, nonmetals, and metalloids) were represented in different colors as in Figure . Then the chemical and physical properties of elements were compared using boxplots.…”

Section: Introductionmentioning

confidence: 99%

Data Visualization Using Boxplots: Comparison of Metalloid, Metal, and Nonmetal Chemical and Physical Properties

Borges

2023

Self Cite

In this activity, students observe chemical and physical properties of elements using an online periodic table, where these properties were shown numerically and by colors. Then the elements were divided into metals, nonmetals, and metalloids, and their periodic properties were visualized using statistical concepts such as normality, kurtosis, histograms, Q−Q plots, p values, and, most important, boxplots. These statistical tests were carried out using JASP, which is free and opensource software written in the R language.