Statistics for Data Science and Business Analysis [Video]

Statistics for Data Science and Business Analysis [Video]

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Statistics you need in the office: Descriptive and inferential statistics, hypothesis testing, and regression analysis
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Video Details

ISBN 13 9781789803259
Course Length 4 hours 19 minutes

Table of Contents

Practical example: descriptive statistics
Practical example: inferential statistics
Practical example: hypothesis testing
Dealing with categorical data
Practical example: regression analysis

Video Description

This course will teach you fundamental skills that will enable you to understand complicated statistical analysis directly applicable to real-life situations. Modern software packages and programming languages are now automating most of these activities, but this course gives you something more valuable—critical thinking abilities. This course will help you understand the fundamentals of statistics, learn how to work with different types of data, calculate correlation and covariance, and more. Careers in the field of data science are some of the most popular in the corporate world today. And, given that most businesses are starting to realize the advantages of working with the data at their disposal, this trend will only continue to grow

Style and Approach

A complete course (packed with extensive case studies, complete training, an HD video, and animations) that covers major statistical topics and helps you become a marketing analyst, a business intelligence analyst, a data analyst, or a data scientist. No prior experience is required for the course.

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What You Will Learn

  • Understand the fundamentals of statistics
  • Work with different types of data
  • How to plot different types of data
  • Calculate the measures of central tendency, asymmetry, and variability
  • Calculate correlation and covariance
  • Distinguish and work with different types of distribution
  • Estimate confidence intervals
  • Perform hypothesis testing
  • Make data-driven decisions
  • Understand the mechanics of regression analysis
  • Carry out regression analysis
  • Use and understand dummy variables
  • Understand the concepts needed for data science even with Python and R!

Authors

Table of Contents

Practical example: descriptive statistics
Practical example: inferential statistics
Practical example: hypothesis testing
Dealing with categorical data
Practical example: regression analysis

Video Details

ISBN 139781789803259
Course Length4 hours 19 minutes
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