Statistics and Hypothesis Testing for Data science
https://DevCourseWeb.com
Published 9/2023
Created by Meritshot Academy
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 31 Lectures ( 4h 15m ) | Size: 3.83 GB
"Mastering Data Analysis and Making Informed Decisions with Statistical Hypothesis Testing in Data Science".
What you'll learn
Fundamental concepts and importance of statistics in various fields.
How to use statistics for effective data analysis and decision-making.
Introduction to Python for statistical analysis, including data manipulation and visualization.
Different types of data and their significance in statistical analysis.
Measures of central tendency, spread, dependence, shape, and position.
How to calculate and interpret standard scores and probabilities.
Key concepts in probability theory, set theory, and conditional probability.
Understanding Bayes' Theorem and its applications.
Permutations, combinations, and their role in solving real-world problems.
Practical knowledge of various statistical tests, including t-tests, chi-squared tests, and ANOVA, for hypothesis testing and inference.
Requirements
Access to a computer with internet connectivity.
A basic understanding of mathematics, including algebra and arithmetic.
Familiarity with fundamental concepts in data analysis and problem-solving.
A willingness to learn and engage with statistical concepts and Python programming.
Basic knowledge of Python is a plus but not mandatory.
