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IBM Statistics Academy - Bootcamp (U4STATWS)

Course Description Schedule Course Outline

Detailed Course Outline

IBM Statistics Academy - Laying the Foundation (U4A01G)

  • Concepts of probability and randomness
  • Random variables
  • Dependency and conditional probability
  • Distributions of random variables
  • Multivariate distributions
  • Descriptive data analytics
  • Statistical hypotheses
  • Statistical testing and interpretation
  • Confidence intervals and random intervals
  • Law of large numbers

IBM Statistics Academy - Entering the Arena (U4A02G)

  • Statistical modelling
  • Factors, dependent variable and covariates
  • Formulating hypotheses
  • Recognizing data types

IBM Statistics Academy - Getting Data (U4A03G)

  • Importing various data types
  • Data transformation
  • Specifying variables
  • Targeting subsets of data
  • Web scraping
  • Reading data from data bases and further sources

IBM Statistics Academy - Finding Insights and Making Predictions - Statistics as your Crystal Ball (U4A04G)

  • Model selection
  • Regression based models
  • Linear regression
  • Non-linear regression
  • Seasonal components
  • Binary regression
  • Classification trees
  • Support vector machines
  • Factor analysis
  • Methods for clustering

IBM Statistics Academy - Think big! Big Data Analytics in your Business (U4A05G)

  • IT solutions to data sets with high memory demand
  • Automated data processing
  • Data mining and exploration
  • Techniques for automated model selection

IBM Statistics Academy - Telling the Story - Show what you did (U4A06G)

  • Designing custom tables
  • Creating custom graphics
  • Shiny in IBM SPSS - interactive graphics and content
  • Presenting and explaining statistical concepts to non-statisticians