Response Time Outlier Game
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This example demonstrates a simple response time game where students chase a button, accumulating and analyzing score data. It involves core math concepts like median, statistical distributions, quartile ranges, and outlier detection. Construction highlights include commands like Append, Q3, Q1, RemoveUndefined, Insert, SD, Median, Min, Max, BoxPlot, Histogram, Mean, Length. Suitable for high school statistics teaching, emphasizing data collection and visualization analysis.
GeoGebra Commands & Parameters
Append({2.1659998893737793, 2.636000156402588, 1.0819997787475586, 10, 1.748000144958496, 1.7639999389648438, 1.4180002212524414, 1.1599998474121094, 1.2300000190734863, 1.8460001945495605, 3.390000343322754, 1.935999870300293, 2.943999767303467, 1.6279997825622559, 3.2950000762939453, 1.6319999694824219, 2.8899998664855957}, 1.6739997863769531) → timesQ3(times) → q3Q1(times) → q1RemoveUndefined(Zip[If[(k ≥ lowfence) ∧ (k ≤ highfence), k], k, times]) → nooutliertimesInsert(false, Insert[true, {false, false, false, false, false, false, false, false}, Min[Random[1, randlimit], limit]], 5) → displaySD(If[outliers, nooutliertimes, times]) → stdevMedian(If[outliers, nooutliertimes, times]) → medianMin(If[outliers, nooutliertimes, times]) → minMax(If[outliers, nooutliertimes, times]) → maxBoxPlot(-1.5, 0.5, times, outliers) → plotHistogram(Sequence[k, k, 0, 10], times, false) → histMean(If[outliers, nooutliertimes, times]) → meanLength(times) → count
AI Drawing Prompt Reference
Visualize a response time game with a dataset and its statistical distribution. Start by plotting the original time series with multiple data points, then calculate and draw a box plot and histogram to represent the data distribution, highlighting outliers. Finally, label the maximum, minimum, mean, median, standard deviation, and quartile ranges next to the charts for statistical analysis.
The prompt above was compiled from the original drawing commands and is for reference only.