Research information

Statement of the problem

This study examines how participants' reaction time changes over a training programme, with the same participants measured repeatedly at three sessions.

Objectives

To describe the reaction_time_ms of the participants.
To determine whether reaction_time_ms differs across the repeated sessions (baseline, week 4, and week 8).

Dataset

repeated_training.csv90 rows × 3 cols

Column	Kind	Distinct
participant	categorical	30
session	categorical	3
reaction_time_ms	numeric	87

Feasibility & estimateFree

✓ Feasibledesign: comparative · via heuristic

Detected a comparative design with 2 analyzable variable(s) and 2 analytical question(s). Recommended 2 statistical test(s). Estimated cost: 29 credits.

Recommended analysis

To describe the reaction_time_ms of the participants.

Descriptive Statistics(reaction_time_ms)

To determine whether reaction_time_ms differs across the repeated sessions (baseline, week 4, and week 8).

Repeated-Measures ANOVA(reaction_time_ms, session)

Dataset Complexity8

Statistical Tests6

AI Interpretation6

Visualizations4

Report Generation5

Total to run29 credits

Estimated runtime: ~40-80 seconds

ResultsComputed

2 tests29 credits

Descriptive Statistics (reaction_time_ms)

n	max	min	std	mean	mode	range	median	variable	variance
90	591.200	387.100	42.785	498.759	446.200	204.100	501.450	reaction_time_ms	1830.571

Repeated-Measures ANOVA (reaction_time_ms, session)

significant

N30p< .001

Partial eta squared0.915

large

n	std	mean	condition
30	37.110	525.680	baseline
30	37.295	499.127	week_4
30	36.465	471.470	week_8

The result is statistically significant (p = 0.0000 < 0.05).

Sphericity was violated (Mauchly's test was significant); the Greenhouse-Geisser correction was applied to the degrees of freedom, and the corrected p-value is reported alongside the uncorrected result.

Reaction Time Across a Training Programme

Publication-ready report

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