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justknimeit-29 - Comparing Distributions between Groups

justknimeit-29 - Comparing Distributions between Groups
Challenge 29: Comparing Distributions between GroupsLevel: EasyDescription: Imagine that you want to compare student test scores to find out whether there are anydifferences between the students' performances in 2020 (group 1) compared to 2019 (group 0). Forexample, you might want to find out whether there is an unusually high number of very good scorescompared to the other year, which could be a sign of cheating. Each student participated in the samethree tests and received three test scores (Score 1, Score 2, and Score 3). How similar are thedistributions of the three scores between the two groups? Which score distribution differs the most?The output should contain a visualization of the conditional distributions and a statistical test for theequality of mean and variance between the groups.Hint: Check out the verified components for visualization on the KNIME Hub. Component - viewer to compare scoresbetween groups Expanded workflow Findings:1) Score 1 has a bimodal distribution. Nonetheless, the means between the two groups(years) are significantly different, even though the variances are found to be not significantlydifferent between the two groups.2) Score 2 has a Gaussian-like distribution. However the means and variances aresignificantly different between the two groups.3) Score 3 has a bimodal distribution. However, both mean and variances do not significantlydiffer between the two groups.The equality of means was tested using independent t-test, with the assumption of equality ofvariances depending on the outcome of the Levene's test.The equality of variances was tested using Levene's test. Displays density plot (i.e. histogram-like) for selected scores between groupsSelect scores to displayFilters group for display (scores)Refresh buttonDisplays box plot for selected scores between groupsFilters rows with the selected scoreFilters rows with the selected scoreFilters the appropriate equal variance assumptionRule engine to determine if variances are equal or not (based on p-value)Convert to flow variableConverts to consistent row IDDisplay whether variances are equal across two groupsUpload scores.tablePerforms independent groups t-testDisplays whether means are equal across two groupsInteractive viewer to compare scores between groupsUpload scores.tableInputs number of binsMerge variables ConditionalDensity Plot Column SelectionWidget Column Filter RefreshButton Widget ConditionalBox Plot Row Filter Row Filter Row Filter Rule Engine Table Columnto Variable RowID Table View Table Reader Independentgroups t-test Table View Viewer Table Reader Integer Widget Merge Variables Challenge 29: Comparing Distributions between GroupsLevel: EasyDescription: Imagine that you want to compare student test scores to find out whether there are anydifferences between the students' performances in 2020 (group 1) compared to 2019 (group 0). Forexample, you might want to find out whether there is an unusually high number of very good scorescompared to the other year, which could be a sign of cheating. Each student participated in the samethree tests and received three test scores (Score 1, Score 2, and Score 3). How similar are thedistributions of the three scores between the two groups? Which score distribution differs the most?The output should contain a visualization of the conditional distributions and a statistical test for theequality of mean and variance between the groups.Hint: Check out the verified components for visualization on the KNIME Hub. Component - viewer to compare scoresbetween groups Expanded workflow Findings:1) Score 1 has a bimodal distribution. Nonetheless, the means between the two groups(years) are significantly different, even though the variances are found to be not significantlydifferent between the two groups.2) Score 2 has a Gaussian-like distribution. However the means and variances aresignificantly different between the two groups.3) Score 3 has a bimodal distribution. However, both mean and variances do not significantlydiffer between the two groups.The equality of means was tested using independent t-test, with the assumption of equality ofvariances depending on the outcome of the Levene's test.The equality of variances was tested using Levene's test. Displays density plot (i.e. histogram-like) for selected scores between groupsSelect scores to displayFilters group for display (scores)Refresh buttonDisplays box plot for selected scores between groupsFilters rows with the selected scoreFilters rows with the selected scoreFilters the appropriate equal variance assumptionRule engine to determine if variances are equal or not (based on p-value)Convert to flow variableConverts to consistent row IDDisplay whether variances are equal across two groupsUpload scores.tablePerforms independent groups t-testDisplays whether means are equal across two groupsInteractive viewer to compare scores between groupsUpload scores.tableInputs number of binsMerge variables ConditionalDensity Plot Column SelectionWidget Column Filter RefreshButton Widget ConditionalBox Plot Row Filter Row Filter Row Filter Rule Engine Table Columnto Variable RowID Table View Table Reader Independentgroups t-test Table View Viewer Table Reader Integer Widget Merge Variables

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Created by: astl3
Created at: 2022-08-10
On NodePit since: 2022-08-12
Last update: 2024-12-24
Created with KNIME version: v4.6.1
Tags: viewerinteractivejustknimeit-29Justknimeit-29statisticsvisualizationbox plot

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