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Overview

Statistics Fundamentals Course Overview

Statistics Fundamentals introduces the foundational concepts needed to run a statistical test and interpret the results. We will overview the landscape of statistics exploring descriptive statistics and various approaches to inferential statistics. You’ll learn not only the types of approaches but also why we need different approaches and how data scientists go about selecting the best approach. In this course, you’ll also get a chance to run hypothesis tests on real and simulated data sets using Excel’s Data Analysis ToolPak. We’ll also examine key fundamental concepts like the Central Limit Theorem, Empirical Rule, and Law of Large Numbers and you’ll apply what you learn through exercises.

The topics covered in this course will support you in conducting good analysis, applying data to business decisions, and exploring the more advanced topics within the Business Intelligence and Data Analysis program such as machine algorithms.

Statistics Fundamentals Learning Objectives

Upon completing this course, you will be able to:

Define and recognize the key branches of statistics
Identify the various approaches to inferential statistics and their strengths and weaknesses
Identify strategies for constructing an unbiased hypothesis test
Assemble and perform a two-tail t-test

Who should take this course?

The Statistics Fundamentals course is perfect for anyone without a background in statistics who would like to build up their understanding or for those who just want a refresher. This course is designed to equip anyone who desires to begin a career in data analysis, quantitative analysis, business intelligence, or other areas of business and finance with an understanding of foundational statistics tools and concepts.

Statistics Fundamentals

Led by Joseph Yeates

Get Started Enroll For Free

Level 2

Approx 3h to complete

100% online and self-paced

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What you'll learn

Lesson

Multimedia

Exams

Files

Course Introduction

Course Introduction Free Preview

Downloadable Files

The Statistical Landscape

Chapter Introduction - Statistical Landscape Free Preview

The Anatomy of a Data Set Free Preview

Descriptive vs Inferential Statistics Free Preview

Approaches to Inferring Probability Free Preview

Interactive Exercise

Assumptions in Inferential Statistics

Interactive Exercise

The Flow Chart

Interactive Exercise

Descriptive Statistics

Chapter Introduction - Descriptive Statistics

Measures of Central Tendency

Interactive Exercise

Measures of Dispersion

Normal Distribution

Interactive Exercise

Kurtosis

Asymmetric (and Other) Distributions

Interactive Exercise

Excel - Univariate Analysis

Univariate vs Bivariate

Correlation

Simple Linear Regression

Interactive Exercise

Excel - Bivariate Analysis

Inferential Statistics

Chapter Introduction - Inferential Statistics

Population & Samples

P-values

Calculating p-values

Alphas & Confidence Levels

Proving a Difference vs Rejecting No Difference

Degerming Sample Size

Law of Large Numbers

Central Limit Theorem

Excel - Law of Large Numbers

Excel - Central Limit Theorem

Controlling for Bias

Hypothesis Testing

Chapter Introduction - Hypothesis Testing

Hypothesis Testing Steps

Stating the Hypothesis

Setting the Alpha & Confidence Level

Selecting the Hypothesis Test

Running a Two-Tailed Hypothesis Test

One-Tailed Test

Running a One-Tailed Hypothesis Test

Errors in Hypothesis Testing

Reporting the Results

Conclusion

Course Summary

Qualified Assessment

This Course is Part of the Following Programs

Why stop here? Expand your skills and show your expertise with the professional certifications, specializations, and CPE credits you’re already on your way to earning.

Business Intelligence & Data Analyst (BIDA)® Certification

Statistics Fundamentals is part of the Business Intelligence & Data Analyst (BIDA)® certification, which includes 25 courses.

Skills Learned Data visualization, data warehousing and transformation, data modeling and analysis
Career Prep Business intelligence analyst, data scientist, data visualization specialist

Learn More

FinTech Industry Professional (FTIP)™

Skills Learned Financial Technology Fundamentals, Data Science and Machine Learning, Cryptocurrencies and Blockchain
Career Prep Data Science and Machine Learning, Data Analyst, Business Analyst, Software Developer

Learn More

What our students say

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My experience which is used to machine information
To provide constructive feedback on how to improve the course, it would be helpful to know more details about its content, format, and your specific experiences or suggestions. Feel free to share any areas you think could be enhanced, and I can offer general recommendations based on the information provided.

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Review
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Statistics Fundamentals

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