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Data Analysis Concepts


Overview/Description
Target Audience
Prerequisites
Expected Duration
Lesson Objectives
Course Number


Overview/Description
There are many software and programming tools available to data scientists. Before applying those tools effectively, you must understand the underlying concepts. In this course, you'll explore the underlying data analysis concepts needed to employ the software and programming tools effectively

Target Audience
Individuals with some programming and math experience working toward implementing data science in their everyday work

Prerequisites
None

Expected Duration (hours)
1.7

Lesson Objectives

Data Analysis Concepts

  • start the course
  • perform basic math operations required by data scientists
  • perform basic vector math operations required by data scientists
  • perform basic matrix math operations required by data scientists
  • perform a matrix decomposition
  • identify different forms of data
  • describe probability in terms of events and sample space size
  • describe basic properties of outcomes
  • apply probability rules in calculation
  • identify common continuous probability distributions
  • identify common discrete probability distributions
  • apply bayes theorem and describe how it is used in email spam algorithms
  • apply random sampling to A/B tests
  • identify and describe various statistical measures
  • describe the difference between an unbiased and biased estimator
  • describe sampling distributions and recognize the central limit theorem
  • define confidence intervals and work with margins of error
  • carrying out hypothesis tests and working with p-values
  • apply the chi-square test for categorical values
  • identify the given data set descriptions by their types
  • Course Number:
    df_dses_a07_it_enus