Key Statistical Concepts

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

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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
Intermediate