Parametric Statistics Explained Simply | Correlation, Regression, SPSS & Real Research Examples

Parametric Statistics Explained Simply

Are statistics confusing?

Have you ever looked at SPSS output, correlation coefficients, regression equations, or research articles and wondered what all those numbers actually mean?

In this video, I break down parametric statistics using plain language, real-world examples, and step-by-step demonstrations designed specifically for students, doctoral researchers, dissertation writers, and anyone learning quantitative research.

You'll learn:

✅ What parametric statistics are

✅ Parametric vs. nonparametric tests

✅ Key assumptions of parametric analysis

✅ Pearson correlation explained

✅ How to interpret correlation coefficients (r)

✅ Linear regression explained simply

✅ Understanding R² (R-Squared)

✅ Reading SPSS output tables

✅ Running regression analysis in SPSS

✅ Common statistical mistakes to avoid

✅ Real-world research applications

Whether you're working on a dissertation, master's thesis, doctoral research project, or simply trying to understand quantitative data analysis, this video will help you build a strong foundation in statistical reasoning.

Remember:

Correlation measures relationships.

Regression predicts outcomes.

SPSS performs calculations.

Researchers provide interpretation.

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⏱️ CHAPTERS / TIMESTAMPS

00:00 Introduction

01:30 What is Parametric Analysis?

03:15 Parametric vs Nonparametric Tests

04:45 Assumptions of Parametric Statistics

06:45 Core Statistical Pillars

07:45 Understanding Correlation

09:15 Interpreting Pearson's r

10:45 Linear Regression Explained

12:45 The Line of Best Fit

14:30 Reading SPSS Output

16:30 Running Regression in SPSS

18:30 Key Takeaways

20:00 Final Thoughts

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