## Description

Essential Statistics for Data Analysis, a statistics course for data analysis, is published by Udemy Academy. This is a hands-on, project-based course designed to help you learn and apply the statistical concepts necessary for data analysis and business intelligence. Our goal is to simplify and minimize the world of statistics by using familiar tools such as Microsoft Excel and empower ordinary people to understand and apply these tools and techniques even if they have no background in mathematics and statistics. We begin by examining the role of statistics in business intelligence, the difference between sample and population data, and the importance of using statistical techniques for intelligent predictions and data-driven decision making.

We then examine our data using descriptive statistics and probability distributions, introduce the normal distribution and the empirical rule, and learn how to apply the central limit theorem to make inferences about populations of any kind. From there we will practice estimation with confidence intervals and the use of hypothesis tests to evaluate hypotheses about unknown population parameters. In the following, we will introduce the basic hypothesis testing framework and then we will discuss concepts such as null and alternative hypothesis, t-scores, p-values, type I errors versus type II errors, etc. Finally, we will introduce the principles of regression analysis, examine the difference between correlation and causality, and practice using basic linear regression models for forecasting using Excel analysis tools.

### What you will learn

• Learn powerful statistical tools and techniques for data analysis and business intelligence
• Understanding how to apply the fundamental concepts of statistics such as the central limit theorem and the empirical rule
• Data analysis with descriptive statistics, including probability distributions and measures of variability and central tendency
• Data modeling and estimation using probability distributions and confidence intervals
• Data-driven decision making and hypothesis testing
• Using linear regression models to discover variable relationships and predict

### Who is this course suitable for?

• Data enthusiasts who want to learn about the world of statistics
• Business intelligence professionals who want to make confident, data-driven decisions
• Anyone who uses data to make assumptions, estimates, or predictions at work
• Students looking to learn powerful and practical skills with unique projects and demos

### Specifications of Essential Statistics for Data Analysis course

• Publisher: Udemy
• teacher : Maven Analytics , Enrique Ruiz
• English language
• Education level: all levels
• Number of courses: 137
• Training duration: 7 hours and 51 minutes

### Course prerequisites

• No math or statistics background is required – we’ll start with the absolute basics!

• We’ll use Microsoft Excel (Office 365) for course projects and demos

### Installation guide

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English subtitle

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