Nonparametric Hypothesis Tests Tutoring – Learn from PhD Expert | Starting $15/Hour
1-on-1 Zoom Sessions All Sessions Recorded Personal Portal Access Flexible Scheduling
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Personalized learning experience designed for your success
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Get personal attention via Zoom video calls. No group classes, no distractions – just you and your expert tutor focused on your learning goals.
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Every session is automatically recorded and stored in your personal portal. Replay any lesson anytime, review concepts, and never miss important details.
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Book sessions at your convenience. Evening slots, weekend availability, and urgent same-day sessions available. We work around your schedule.
- 7 days a week availability
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No rush, no judgment, no pressure. We adapt our teaching style to match your learning speed and preferences. Ask questions freely until you understand.
- Adaptive teaching methods
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Transparent Pricing – Choose Your Learning Plan
Flexible hourly rates based on your needs and subject complexity
Beginner
Perfect for Basic Concepts
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- Basic Statistics Concepts
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Non-Parametric Statistics Tutoring – Master Distribution-Free Tests
Learn all major non-parametric methods for when your data doesn’t meet parametric assumptions
Non-Parametric Test Topics
- Parametric vs Non-Parametric: When to Choose
- Mann-Whitney U Test (Wilcoxon Rank-Sum)
- Wilcoxon Signed-Rank Test (Paired Data)
- Kruskal-Wallis H Test (Multiple Groups)
- Friedman Test (Repeated Measures)
- Chi-Square Tests for Categorical Data
- Spearman & Kendall Correlation
- Sign Test & Median Test
- Kolmogorov-Smirnov & Shapiro-Wilk Tests
- McNemar’s Test & Cochran’s Q Test
Software & Practical Skills
- Testing Assumptions Before Choosing a Test
- Effect Size for Non-Parametric Tests
- Non-Parametric Tests in SPSS
- R Functions (wilcox.test, kruskal.test)
- Python (scipy.stats Non-Parametric Module)
- Interpreting Rank-Based Test Output
- Comparing Results with Parametric Alternatives
- Reporting Non-Parametric Results (APA)
- Post-Hoc Tests for Kruskal-Wallis & Friedman
- Real-World Non-Parametric Practice Problems
What You’ll Achieve with Non-Parametric Tutoring
Know When to Go Non-Parametric
Confidently decide when parametric assumptions are violated and non-parametric alternatives are needed.
Select the Right Test
Match the correct non-parametric test to your research design – independent groups, paired, or multiple comparisons.
Calculate by Hand & Software
Understand how rank-based tests work mathematically and run them efficiently in SPSS, R, or Python.
Interpret Outputs Correctly
Read and understand non-parametric test statistics, p-values, and effect sizes with confidence.
Report Results Professionally
Present non-parametric findings following academic reporting standards with proper notation and effect sizes.
Excel in Coursework & Research
Build complete non-parametric skills needed for statistics courses, research projects, and dissertations.
Non-Parametric Methods Made Clear
Non-parametric tests are essential when your data is skewed, has outliers, contains ordinal measurements, or simply doesn’t meet the assumptions required by parametric tests. Yet many students find these methods confusing because they seem like an afterthought in most textbooks. Our tutoring gives non-parametric methods the attention they deserve – explaining the logic of rank-based tests, when each one applies, and how to implement and report them properly. Perfect for researchers working with small samples, psychology and social science students, and anyone whose data doesn’t fit neatly into parametric frameworks.
Master non-parametric statistics today!