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Zero To Mastery

Introduction to Inferential Statistics

via Zero To Mastery Path

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Overview

Learn real-world inferential statistics with Python including confidence intervals, hypothesis testing, and hands-on projects to build your data skills from the ground up.
  • How to use Python for real-world statistical analysis
  • Understand and apply confidence intervals
  • Master hypothesis testing techniques step-by-step
  • Use statistical thinking to make data-driven decisions
  • Explore t-tests, z-scores, ANOVA, and more
  • Spot and avoid common statistical errors
  • Build reusable Python functions for statistical tests
  • Work through hands-on projects using real datasets

Syllabus

  •   Introduction
    • Introduction
    • Exercise: Meet Your Classmates and Instructor
    • Resources - Download Course Materials
  •   Descriptive Statistics
    • Game Plan for Descriptive Statistics
    • Variable Types in Statistics
    • QUIZ - Variable Types
    • QUIZ - Variable Types - Explanations
    • Population vs. Sample
    • CASE STUDY Briefing - Moneyball
    • Python - Setting Up
    • Measures of Central Tendency
    • (Arithmetic) Mean
    • Python - Mean
    • EXERCISE - Mean
    • Median
    • Python - Median
    • EXERCISE - Median
    • Mode
    • Python - Mode
    • EXERCISE - Mode
    • Standard Deviation and Variance
    • Python - Standard Deviation and Variance
    • EXERCISE - Standard Deviation and Variance
    • Coefficient of Variation
    • EXERCISE - Coefficient of Variation
    • Python - Coefficient of Variation
    • Covariance
    • Python - Covariance
    • EXERCISE - Covariance
    • Correlation
    • Python - Correlation
    • EXERCISE - Correlation
    • Normal Distribution
    • Python - Normal Distribution
    • EXERCISE - Normal Distribution
    • PRACTICE TEST: Descriptive Statistics
    • PRACTICE TEST: Descriptive Statistics - Explanations
    • CASE STUDY - Moneyball
    • Wrap Up - Descriptive Statistics
    • Implement a New Life System
  •   Confidence Intervals
    • Game Plan for Confidence Intervals
    • CASE STUDY Briefing - Dioguinis Pizza
    • Standard Error of the Sample Mean
    • Python - Libraries and Data
    • Python - Standard Error of the Sample Mean
    • Z-Score and Standardization
    • Python - Z-Score and Standardization
    • Confidence Level
    • Python - Confidence Level
    • Confidence Intervals for Large Samples
    • Python - Confidence Interval for Large Samples
    • EXERCISE - Confidence Interval Function with ChatGPT
    • CASE STUDY - Guinness Beer and t-distribution
    • Degrees of Freedom
    • Confidence Interval with Small Samples
    • Python - Confidence Interval with Small Samples
    • EXERCISE - Confidence Interval Function with ChatGPT
    • PRACTICE TEST: Confidence Intervals
    • PRACTICE TEST - Confidence Intervals - Explanations
    • Confidence Intervals Wrap Up
  •   Capstone Project - Lights, Camera, Statistics!
    • Project Presentation - Lights, Camera, Statistics
    • Python - Data Preparation and Cleaning
    • Python - Exploratory Data Analysis
    • Python - Estimating Average Ratings
    • Python - Conclusions
    • Exercise: Imposter Syndrome
  •   Hypothesis Testing
    • Game Plan for Hypothesis Testing
    • What is Hypothesis Testing?
    • QUIZ - Hypothesis Testing
    • QUIZ - Hypothesis Testing - Explanations
    • P-Value
    • QUIZ - P-value
    • QUIZ - P-value - Explanations
    • Type I and Type II Errors
    • QUIZ - Type I and Type II Errors
    • QUIZ - Type I and Type II Errors - Explanations
    • CASE STUDY - Publication Bias in Statistics
    • How to Test Your Hypothesis (Known Population Variance).
    • CASE STUDY Briefing - Tesla Production
    • Python - Setting Up and Libraries
    • Python - How to Test Your Hypothesis (Known Population Variance)
    • Python - Build a Function to Test Your Known Variance Hypothesis
    • Hypothesis Testing with Unknown Population Variance
    • Python - How to Test Your Hypothesis (Unknown Population Variance) - Part 1
    • Python - How to Test Your Hypothesis (Unknown Population Variance) - Part 2
    • Paired T-Test
    • Python - Paired T-Test - Part 1
    • Python - Paired T-Test - Part 2
    • Two Sample T-Test
    • Python - Levene's Test
    • Python - Welch's T-Test
    • Python - Two-Sample T-Test
    • Exercise - Two-Sample Test Function
    • One-Tailed Test vs. Two-Tailed Test
    • Python - One-Tailed Test with Known Variance
    • Python - One-Tailed Test with Unknown Variance
    • Python - One-Tailed Paired T-Test
    • Python - One-Tailed Two-Sample T-Test
    • Chi-Square Test
    • Python - Chi-Square Test
    • Is Your Distribution Normal? - The Shapiro-Wilks Test
    • Python - Shapiro-Wilks Test
    • PRACTICE TEST - Hypothesis Testing
    • PRACTICE TEST - Hypothesis Testing - Explanations
    • Powerposing and P-Hacking
    • Hypothesis Testing Wrap Up
  •   Capstone Project - ChatGPT Data Analysis
    • Capstone Project with ChatGPT - Yelp me!
    • Python Solutions - Data
    • Python Solutions - Hypothesis 1
    • Python Solutions - Hypothesis 2
    • Python Solutions - Hypothesis 3
  •   Advanced Hypothesis Testing
    • Game Plan for Advanced Hypothesis Testing
    • Python - Setup
    • Mann-Whitney U Test
    • Python - Box plot for Normality
    • Python - Shapiro Wilks Test
    • D'Agostino and Pearson Test
    • Python - D'Agostino and Pearson Test
    • Python - Mann-Whitney U Test
    • ANOVA
    • Python - ANOVA
    • Python - D'Agostino and Pearson Test
    • Kruskal-Wallis Test
    • Python - Kruskal-Wallis Test
    • Spearman Correlation
    • Python - Spearman Correlation
    • Wilcoxon Signed-Rank Test
    • Python - Wilcoxon Signed-Rank Test
    • Key Learnings and Outcomes - Advanced Hypothesis Testing
  •   Where To Go From Here?
    • Let's Keep Learning Together!
    • Review This Byte!

Taught by

Diogo Resende

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