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Google

The Power of Statistics

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Overview

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Uncover how data professionals utilize statistics to analyze data, gain key insights, and communicate findings effectively. This course explores descriptive and inferential statistics, probability, sampling, confidence intervals, hypothesis testing, and Python for statistical analysis. Google employees provide hands-on activities, sharing real-world examples to enhance your data analytics skills for your career. This is the fourth course in the Google Advanced Data Analytics Certificate, a series designed to prepare you for an advanced data analytics role.

Syllabus

  • Introduction to statistics with Python
    • Introduction to Course 3
    • Evan: Engage and connect
    • Course 3 overview
    • Welcome to module 1
    • The role of statistics in data science
    • Statistics in action: A/B testing
    • Descriptive statistics versus inferential statistics
    • Practice Quiz: Test your knowledge: The role of statistics in data science
    • Measures of central tendency
    • Measures of central tendency: The mean, the median, and the mode
    • Measures of dispersion
    • Measures of dispersion: Range, variance, and standard deviation
    • Measures of position
    • Measures of position: Percentiles and quartiles
    • Alok: Statistics as the foundation of data-driven solutions
    • Practice Quiz: Test your knowledge: Descriptive statistics
    • Compute descriptive statistics with Python
    • Activity: Introduction to statistics
    • Exemplar: Introduction to statistics
    • Practice Quiz: Test your knowledge: Calculate statistics with Python
    • Wrap-up
    • Glossary terms from module 1
    • Graded Quiz: Module 1 challenge
  • Probability
    • Welcome to module 2
    • Objective versus subjective probability
    • The principles of probability
    • Fundamental concepts of probability
    • The basic rules of probability and events
    • The probability of multiple events
    • Practice Quiz: Test your knowledge: Basic concepts of probability
    • Conditional probability
    • Calculate conditional probability for dependent events
    • Discover Bayes' theorem
    • The expanded version of Bayes’s theorem
    • Calculate conditional probability with Bayes's theorem
    • Practice Quiz: Test your knowledge: Conditional probability
    • Introduction to probability distributions
    • The binomial distribution
    • The Poisson distribution
    • Discrete probability distributions
    • Practice Quiz: Test your knowledge: Discrete probability distributions
    • The normal distribution
    • Model data with the normal distribution
    • Standardize data using z-scores
    • Practice Quiz: Test your knowledge: Continuous probability distributions
    • Work with probability distributions in Python
    • Activity: Probability
    • Exemplar: Probability
    • Practice Quiz: Test your knowledge: Probability distributions with Python
    • Wrap-up
    • Glossary terms from module 2
    • Graded Quiz: Module 2 challenge
  • Sampling
    • Welcome to module 3
    • Cliff: Value everyone's contributions
    • Introduction to sampling
    • The relationship between sample and population
    • The sampling process
    • The stages of the sampling process
    • Compare sampling methods
    • Probability sampling methods
    • The impact of bias in sampling
    • Non-probability sampling methods
    • Practice Quiz: Test your knowledge: Introduction to sampling
    • How sampling affects your data
    • The central limit theorem
    • Infer population parameters with the central limit theorem
    • The sampling distribution of the proportion
    • The sampling distribution of the mean
    • Practice Quiz: Test your knowledge: Sampling distributions
    • Sampling distributions with Python
    • Activity: Sampling
    • Exemplar: Sampling
    • Practice Quiz: Test your knowledge: Work with sampling distributions in Python
    • Wrap-up
    • Glossary terms from module 3
    • Graded Quiz: Module 3 challenge
  • Confidence intervals
    • Welcome to module 4
    • Introduction to confidence intervals
    • Interpret confidence intervals
    • Confidence intervals: Correct and incorrect interpretations
    • Practice Quiz: Test your knowledge: Introduction to confidence Intervals
    • Construct a confidence interval for a proportion
    • Construct a confidence interval for a mean
    • Construct a confidence interval for a small sample size
    • Practice Quiz: Test your knowledge: Construct confidence intervals
    • Confidence intervals with Python
    • Activity: Confidence intervals
    • Exemplar: Confidence intervals
    • Practice Quiz: Test your knowledge: Work with confidence intervals in Python
    • Wrap-up
    • Glossary terms from module 4
    • Graded Quiz: Module 4 challenge
  • Introduction to hypothesis testing
    • Welcome to module 5
    • Elea: Keep learning in the ever-changing data space
    • Introduction to hypothesis testing
    • Differences between the null and alternative hypotheses
    • Type I and type II errors
    • Practice Quiz: Test your knowledge: Introduction to hypothesis testing
    • One-sample test for means
    • Determine if data has statistical significance
    • Practice Quiz: Test your knowledge: One-sample tests
    • Two-sample tests: Means
    • One-tailed and two-tailed tests
    • Two-sample tests: Proportions
    • A/B testing
    • Experimental Design
    • Case study: Ipsos: How a market research company used A/B testing to help advertisers create more effective ads
    • Practice Quiz: Test your knowledge: Two-sample tests
    • Use Python to conduct a hypothesis test
    • Activity: Introduction to hypothesis testing
    • Exemplar: Introduction to hypothesis testing
    • Practice Quiz: Test your knowledge: Hypothesis testing with Python
    • Wrap-up
    • Glossary terms from module 5
    • Graded Quiz: Module 5 challenge
  • Course 3 end-of-course project
    • Welcome to module 6
    • Sean: Showcase your talents to potential employers
    • Introduction to your Course 3 end-of-course portfolio project
    • Explore your Course 3 workplace scenarios
    • Course 3 end-of-course portfolio project overview: Automatidata
    • Practice Quiz: Activity: Create your Course 3 Automatidata project
    • Activity: Automatidata project lab 3
    • Activity Exemplar: Create your Course 3 Automatidata project
    • Exemplar: Automatidata project lab 3
    • Course 3 end-of-course portfolio project overview: TikTok
    • Practice Quiz: Activity: Create your Course 3 TikTok project
    • Activity: TikTok project lab 3
    • Activity Example: Create your Course 3 TikTok project
    • Exemplar: TikTok project lab 3
    • Course 3 end-of-course portfolio project overview: Waze
    • Practice Quiz: Activity: Create your Course 3 Waze project
    • Activity: Waze project lab 3
    • Activity Exemplar: Create your Course 3 Waze project
    • Exemplar: Waze project lab 3
    • End-of-course project wrap-up and tips for ongoing career success
    • Graded Quiz: Assess your Course 3 end-of-course project
    • Course 3 glossary
    • Course wrap-up
    • Get started on the next course
    • Course 3 resources and citations

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