Business Statistics - Sampling Methods with Python and Excel

Business Statistics - Sampling Methods with Python and Excel udemy course

Learn Sampling Techniques with Hands on Python and Excel – Random, Stratified, Cluster, and More!

Unlock the power of Business Statistics by mastering sampling techniques with Python and Excel! This course provides a practical, hands-on approach to understanding statistics and its applications in real-world data analysis.

What You’ll Learn:

Introduction to Statistics – Understand key statistical concepts and why sampling is crucial for data-driven decision-making.

Types of Sampling Methods:

1. Convenience Sampling – Quick and easy data collection.

2. Simple Random Sampling – Every data point has an equal chance of being selected.

3. Systematic Sampling – Selecting every ‘nth’ data point from a dataset.

4. Stratified Sampling – Dividing data into meaningful subgroups before sampling.

5. Cluster Random Sampling – Random selection of entire groups instead of individuals.

Key Highlights:

• Hands-on Implementation in Python – Apply each sampling method using pandas and NumPy for real-world datasets.

• Sampling in Excel – Learn how to generate and analyze samples using Excel’s built-in statistical tools.

• Comparing Python vs. Excel Approaches – Explore the strengths, differences, and best use cases for each tool.

• Real-World Business Applications – Learn how businesses use sampling to improve decision-making, reduce costs, and optimize strategies.

• Practical Exercises and Case Studies –Relevant examples to solidify your understanding.

  
  

By the end of this course, you’ll be confident in using Python and Excel for statistical sampling, enabling you to make better, data-driven decisions.

Who Should Enroll?

• Business Analysts, Data Enthusiasts, and Students.

• Professionals looking to enhance their data analytics skills.
  Anyone interested in statistical methods and data science.

Join now and take your business statistics skills to the next level!