Course details

Key Statistical Concepts

Key Statistical Concepts


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



Overview/Description
Predictive analytics involves a wide range of statistical tools and methods that allow an analyst to build a powerful predictive model. Explore the importance of statistics and probability theory in predictive analytics.

Target Audience
All individuals who are new to predictive analytics and wish to use it to optimize their business performance; business leaders; analysts; marketing, sales, software, and IT professionals who want to add predictive analytics to their skill set; and decision makers of any kind

Prerequisites
None

Expected Duration (hours)
1.0

Lesson Objectives

Key Statistical Concepts

  • start the course
  • recognize the role of statistics in predictive analytics
  • recognize attributes of qualitative, quantitative, discrete, and continuous data
  • recognize features of data measurement scales
  • recognize features of descriptive and inferential statistics
  • recognize basic features of probability and the types of probabilistic events
  • apply addition and multiplication rules for a probabilistic event
  • apply Bayes theorem in a given situation
  • distinguish between permutations and combinations
  • recognize how to reduce the margin of error
  • recognize how confidence intervals (CI) are used for hypothesis testing
  • recognize key features of testing for differences in mean and testing for differences in proportion
  • determine if a data sample is representative of the data population
  • Course Number:
    df_prma_a03_it_enus

    Expertise Level
    Everyone