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Sample study · comparative design

Student Outcomes Study

Research information

Statement of the problem

This study examines student academic outcomes.

Objectives

To describe the age, study_hours, gpa, and satisfaction of the respondents.
To determine the relationship between study_hours and gpa.
To determine the relationship between age and gpa.
To determine whether gpa differs across the program groups.
To determine whether study_hours differs across the program groups.
To determine the association between gender and civil_status.
To determine the association between gender and program.

Dataset

survey.csv40 rows × 8 cols

Column	Kind	Distinct
respondent	numeric	40
gender	categorical	2
civil_status	categorical	2
program	categorical	3
age	numeric	9
study_hours	numeric	24
gpa	numeric	35
satisfaction	numeric	5

Feasibility & estimateFree

✓ Feasibledesign: comparative · via heuristic

Detected a comparative design with 7 analyzable variable(s) and 7 analytical question(s). Recommended 8 statistical test(s). Estimated cost: 77 credits.

Recommended analysis

To describe the age, study_hours, gpa, and satisfaction of the respondents.

Descriptive Statistics(age, study_hours, gpa)

Frequency & Percentage Distribution(satisfaction)

To determine the relationship between study_hours and gpa.

Pearson Correlation(study_hours, gpa)

To determine the relationship between age and gpa.

Pearson Correlation(age, gpa)

To determine whether gpa differs across the program groups.

One-Way ANOVA(gpa, program)

Tukey HSD Post-Hoc(gpa, program)

Games–Howell Post-Hoc(gpa, program)

Dunn's Test (post-hoc)(gpa, program)

To determine whether study_hours differs across the program groups.

One-Way ANOVA(study_hours, program)

Tukey HSD Post-Hoc(study_hours, program)

Games–Howell Post-Hoc(study_hours, program)

Dunn's Test (post-hoc)(study_hours, program)

To determine the association between gender and civil_status.

Chi-Square Test of Independence(gender, civil_status)

To determine the association between gender and program.

Chi-Square Test of Independence(gender, program)

Dataset Complexity13

Statistical Tests28

AI Interpretation21

Visualizations10

Report Generation5

Total to run77 credits

Estimated runtime: ~1-2 minutes

ResultsComputed

9 tests77 credits

Descriptive Statistics (age, study_hours, gpa)

n	max	min	std	mean	mode	range	median	variable	variance
40	29	19	2.725	21.750	20	10	20.500	age	7.423
40	37	2	8.759	14.800	8	35	14	study_hours	76.728
40	3.890	1.380	0.662	2.579	1.910	2.510	2.605	gpa	0.438

Frequency & Percentage Distribution (satisfaction)

satisfaction · 430.0%

satisfaction · 330.0%

satisfaction · 520.0%

satisfaction · 210.0%

satisfaction · 110.0%

Pearson Correlation (study_hours, gpa)

significant

r.739df38R².546N40p< .001

Pearson r0.739

large

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

Spearman Rank Correlation (age, gpa)

n.s.

r-.014df38R².000N40p.933

Spearman r-0.014

negligible

The result is not statistically significant (p = 0.9328 >= 0.05).

Spearman Rank Correlation was used instead of the Pearson Correlation because the latter's assumption(s) were not met (Normality of age (Shapiro-Wilk)).

One-Way ANOVA (gpa, program)

significant

p.015

Eta squared0.203

small

n	std	mean	group
14	0.669	2.219	A
13	0.580	2.611	B
13	0.560	2.935	C

The result is statistically significant (p = 0.0150 < 0.05).

Tukey HSD Post-Hoc (gpa, program)

pair	p value	mean diff	significant
A vs B	0.228	-0.391	false
A vs C	0.011	-0.715	true
B vs C	0.371	-0.324	false

Pairwise comparisons with family-wise error control (Tukey HSD).

One-Way ANOVA (study_hours, program)

n.s.

p.633

Eta squared0.024

negligible

n	std	mean	group
14	9.385	13.071	A
13	9.045	15.154	B
13	8.128	16.308	C

The result is not statistically significant (p = 0.6332 >= 0.05).

Chi-Square Test of Independence (gender, civil_status)

n.s.

χ²1.844df1N40p.175

Cramér's V0.215

small

row	Single	Married
F	20	5
M	15	0

The result is not statistically significant (p = 0.1745 >= 0.05).

50% of expected cell counts are < 5; Chi-Square may be unreliable. · Fisher's Exact fallback: odds ratio = inf, p = 0.1372.

Chi-Square Test of Independence (gender, program)

n.s.

χ²0.029df2N40p.985

Cramér's V0.027

negligible

A	B	C	row
9	8	8	F
5	5	5	M

The result is not statistically significant (p = 0.9855 >= 0.05).

33% of expected cell counts are < 5; Chi-Square may be unreliable.

Report

Publication-ready report

Tests used · Results · Discussion — generated from the computed statistics.

Every claim checked · 45 numbers verified · 6 findings cross-checked · prose: llm:gemini

Open report ↗Download DOCX Download PDF

Reproducible code

Download the exact Jupyter notebook or Python script that reproduces these results with widely-used libraries (scipy, statsmodels, lifelines).

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