Udemy – Applied Statistics Real World Problem Solving 2024-8

Published on: 2024-09-10 13:21:58

Categories: 28

Description

Applied Statistics Real World Problem Solving course. This is a comprehensive course designed to equip you with the statistical tools and techniques needed to analyze real data and make informed decisions. Whether you are a business analyst, data scientist or simply looking to improve your data analysis skills, this course will provide you with a solid foundation in applied statistics.

What you will learn

Understanding and Differentiating Data Types in Statistics: Gain a thorough understanding of different data types and their applications in business statistics.
Applying Measures of Centrality and Dispersion: Learn how to calculate and interpret the mean, median, frequency, standard deviation, and more.
Hypothesis Testing and Confidence Intervals: Gain the skills to perform hypothesis tests and calculate confidence intervals using real data.
Analyzing relationships between variables: Develop the ability to use correlation coefficients, scatter plots, and advanced statistical techniques to identify and understand relationships between variables.

Who is this course suitable for?

Business Analysts: Looking to sharpen their data analysis skills to make better decisions.
Students and professionals: interested in mastering applied statistics for career advancement.
Researchers: Academics and researchers who need to use statistical methods in their work to achieve accurate results.
Data Scientists: People who seek to apply statistical techniques to solve complex problems.

Specifications of Applied Statistics Real World Problem Solving course

Publisher: Udemy
Instructor: Akhil Vydyula
Training level: beginner to advanced
Training duration: 3 hours and 2 minutes
Number of courses: 16

Course headings

Applied Statistics Real World Problem Solving

Prerequisites of Applied Statistics Real World Problem Solving course

Basic understanding of mathematics: A fundamental knowledge of mathematics is helpful but not mandatory.
Interest in data analysis: A keen interest in learning how to analyze and interpret data effectively.
No programming experience needed: You will learn everything you need to know about applied statistics without any prior programming experience.