Udemy - Statistics and Hypothesis Testing for Data science

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[ DevCourseWeb.com ] Udemy - Statistics and Hypothesis Testing for Data science
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1. Introduction to Statistics
    • 1. Introduction to Statistics and its importance.mp4 (106.8 MB)
    • 2. Explain the role of statistics in data analysis.mp4 (88.7 MB)
    • 3. Introduction to Python for Statistical Analysis.mp4 (92.5 MB)
    2. Introduction to Descriptive Statistics
    • 1. Types of Data.mp4 (126.7 MB)
    • 2. Measures of Central Tendency.mp4 (105.0 MB)
    • 3. Measures of Spread.mp4 (71.2 MB)
    • 4. Measures of Dependence.mp4 (73.9 MB)
    • 5. Measures of Shape and Position.mp4 (145.5 MB)
    • 6. Measures of Standard Scores.mp4 (78.7 MB)
    3. Introduction to Basic and Conditional Probability
    • 1. Introduction to Basic Probability.mp4 (176.2 MB)
    • 2. Introduction to Set Theory.mp4 (106.5 MB)
    • 3. Introduction to Conditional Probability.mp4 (74.7 MB)
    • 4. Introduction to Bayes Theorem.mp4 (118.0 MB)
    • 5. Introduction to Permutations and Combinations.mp4 (112.4 MB)
    • 6. Introduction to Random Variables.mp4 (80.7 MB)
    • 7. Introduction to Probability Distribution Functions.mp4 (202.6 MB)
    4. Introduction to Inferential Statistics
    • 1. Introduction to Normal Distribution.mp4 (215.8 MB)
    • 10. Introduction to Sampling Methods.mp4 (256.5 MB)
    • 2. Introduction to Skewness and Kurtosis.mp4 (143.8 MB)
    • 3. Introduction to Statistical Transformations.mp4 (212.5 MB)
    • 4. Introduction to Sample and Population Mean.mp4 (73.5 MB)
    • 5. Introduction to Central Limit Theorem.mp4 (75.2 MB)
    • 6. Introduction to Bias and Variance.mp4 (114.3 MB)
    • 7. Introduction to Maximum Likelihood Estimation.mp4 (101.7 MB)
    • 8. Introduction to Confidence Intervals.mp4 (78.2 MB)
    • 9. Introduction to Correlations.mp4 (270.6 MB)
    5. Introduction to Hypothesis Testing
    • 1. 1. Fundamentals of Hypothesis Testing.mp4 (108.8 MB)
    • 2. Introduction to T Tests.mp4 (138.7 MB)
    • 3. Introduction to Z Tests.mp4 (88.5 MB)
    • 4. Introduction to Chi Squared Tests.mp4 (232.0 MB)
    • 5. Introduction to Anova Tests.mp4 (54.1 MB)
    • Bonus Resources.txt (0.4 KB)

Description

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.



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Udemy - Statistics and Hypothesis Testing for Data science

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3.8 GB
seeders:1
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Udemy - Statistics and Hypothesis Testing for Data science

Torrent hash: 1BD607F1AE34C7089E1AA7E4413720F70707CA33