Statistics for Data Science. |Course hero helper

Posted: March 7th, 2023

Statistics for Data Science.

1. Current occupation and employer (if applicable)
2. Experience and/or background with statistics

Why study statistics?

Modern computing power is causing a revolution in data analysis. Key drivers have been the rapid development of new technology, access to more and bigger data, and the greater use of quantitative analysis in a variety of disciplines:

1. Why is computing power so influential in data analysis?
2. Why is almost any sort of data so valuable to the companies and the governments?

• Complete the discussion by the assigned due date.
• Do not claim credit for the words, ideas, and concepts of others.
• Do not copy and paste information or concepts from the Internet and claim that it is your work. It will be considered Plagiarism and you will receive a zero for your work.

SOLUTION

Statistics is essential in data science because it provides the tools and methods to extract insights and knowledge from data. It helps us to summarize, analyze, and interpret large and complex datasets, providing a framework for making data-driven decisions. Modern computing power is influential in data analysis because it allows us to process and analyze vast amounts of data quickly and efficiently. With the increasing availability of big data and advancements in machine learning and artificial intelligence, we can extract insights from data that were previously impossible.