Sampling, Central Limit Theorem, & Standard Error

Course Overview

• Course Title: Sampling, Central Limit Theorem, & Standard Error
• Instructor: Robert (Bob) Steele
• Target Audience:
  • Beginners in statistical methods
  • Students interested in data analysis
  • Professionals seeking foundational statistical knowledge
• Prerequisites:
  • General comfort with numbers and quantitative reasoning
  • Ability to read and interpret graphs, charts, and tables
  • Willingness to think critically and explore data patterns

Curriculum Highlights

• Key Topics Covered:
  • Defining key statistical terms
  • Sampling methods (simple random, stratified, cluster)
  • Sampling bias and minimizing error
  • Central Limit Theorem significance
  • Calculating standard error
  • Evaluating sample representativeness
  • Integrating statistical methods for inference
  • Justifying statistical conclusions
• Key Skills Learned:
  • Interpreting statistical language and concepts
  • Differentiating sampling methods
  • Minimizing sampling error
  • Applying the Central Limit Theorem
  • Analyzing standard error
  • Assessing sample variability
  • Drawing valid statistical inferences
  • Critical thinking in statistical analysis

Course Format

• Duration: 4.5 hours on-demand video
• Format: Self-paced online course
• Resources:
  • 1 article
  • 3 downloadable resources
  • Access on mobile and TV
  • Certificate of completion

Special Offer (If Applicable)

• Limited Time Coupon Code: N/A