Likert Scale questionnaires in Business Research with Python

A step-by-step approach to Implementing, analyzing and reporting Likert scale questionnaire

What you'll learn
- Overview of problem statement, research objectives, HRM practices' impact on firm performance, study significance and development of research hypotheses
- Research framework, research questions, hypothesis development and Likert scales questionnaire preparation
- Data import, missing value treatment, variable recoding, and composite score calculation
- Scale reliability testing using Cronbach's Alpha for all constructs
- Descriptive Statistics and demographic profile of respondents with visualizations
- Hypothesis Testing on each of the HRM Practice against the Firm Performance using Pearson correlation analysis
- Multiple regression analysis testing integrated impact of all HRM practices
- ANOVA and T-tests examining how firm performance varies across demographic groups
- Comprehensive analysis of all four hypothesis testing outcomes
- Summary of significant relationships, effect sizes, and explanatory power
- Summary of main findings, theoretical contributions and practical recommendations for HR managers and organizational leaders

Requirements
- No programming experience required but basics of Python will be added advantage
- Basic knowledge of Social science subject such as Business, Management, etc.

Description
In today's data-driven business world, the ability to transform complex information into actionable insights is no longer just a "nice-to-have" skill—it's a career superpower. Whether you're a manager making strategic decisions, a researcher conducting studies, or a professional seeking to validate business strategies, statistical analysis is your most valuable tool.

But here's the reality most courses don't tell you:Learning statistics in isolation is frustrating and ineffective. Watching theoretical lectures without applying concepts to real business problems leaves you unprepared for the challenges you'll face in your career.

Why This Course is Different

This isn't just another statistics course. This is acomplete research journeywhere you'll solve a real business problem from start to finish:

We'll investigate the critical question:"How do HRM practices—Training, Motivation, and Leadership—impact firm performance?"

This isn't a hypothetical exercise. This is the same type of analysis that drives million-dollar business decisions in organizations worldwide.

The Problem We Solve Together

Imagine you've collected survey data from employees. You have:

190 respondentswith diverse demographics

11 measurement variablesacross four key constructs

Multiple research hypothesesto test

Stakeholders waitingfor data-driven recommendations

How do you transform this raw data into compelling business insights?

That's exactly what you'll master in this course. You'll learn the complete workflow that top consultants and researchers use—not just the statistical tests, but the entire process from data cleaning to executive reporting.

What Makes This Approach Unique

Programming Tool Workflow:We recognize that professionals need flexibility. You'll master:

Pythonfor data science and visualization using Jupyter Notebook

FullPython codefor download

Completedatasetfor practice

Real Business Context:Every analysis answers a real business question. You're not just learning statistical tests—you're learning how to solve business problems with data.

From Theory to Implementation:We bridge the gap between statistical concepts and practical application. You'll understand not justhowto run tests, butwhenandwhy—and most importantly,how to interpret results for business impact.

What You'll Achieve

By the end of this course, you won't just understand statistical concepts—you'll have:

·Completed a full research projectfrom data to decisions

·Mastered the statistical toolsfor any analysis situation

·Built a professional portfolio piecedemonstrating your analytical capabilities

·Gained confidenceto tackle any business research challenge

·Developed a repeatable frameworkfor future data analysis projects

Who this course is for:
- Business Students learning research methods
- HR Professionals wanting data-driven insights
- Managers needing to make evidence-based decisions
- Researchers conducting organizational studies
- Data Analysts expanding their statistical toolkit
- Academic Researchers preparing publications
- Consultants delivering data-backed recommendations
More Info