Statistics For Business Analytics: Data Analysis With Excel

Improve your Statistics & Analysis Skills. Enhance your Business and Data Analytics with Statistical Modelling & Excel.

What you'll learn
Comprehend the fundamental concepts and principles of statistics and their application in business analytics
Complete several data analysis projects in Excel to demonstrate mastery of statistical concepts and business analytics skills
Perform data analysis using Excel and apply statistical methods to business problems
Utilize Excel to perform hypothesis testing and make decisions based on business data
Analyze business data using descriptive and inferential statistics in Excel
Construct and interpret statistical models to make informed business decisions
Implement regression analysis in Excel to predict future trends and make data-driven decisions
Utilize data analytics techniques to analyze large datasets and extract meaningful insights
Evaluate real-world business scenarios and critically assess the use of statistical models and data analytics
Analyze data using linear regression techniques in Excel to make predictions and understand relationships

Requirements
Basic Excel knowledge is desirable

Description
Data is everywhere and plays a crucial role in the success of businesses across all industries. As the world becomes more and more data-driven, the demand for professionals who can effectively analyze and interpret data is growing rapidly. If you're ready to take your place at the forefront of this exciting and rapidly evolving field, "Statistics for Business Analytics: Data Analysis with Excel" is the course for you!This comprehensive online course is designed for anyone looking to develop their skills in data analysis, statistical modeling, and business analytics. Whether you're just starting out or looking to advance your career, this course will provide you with the knowledge and hands-on experience you need to succeed.With its engaging curriculum, practical case studies, and supportive community, this course is the perfect opportunity to build your skills, advance your career, and stay ahead of the curve in a rapidly changing landscape. Here are four reasons why you should take this course:1 | Course Relevance - Stay Ahead of the Curve in a Data-Driven World In today's business world, having a solid understanding of statistics and data analysis is more important than ever. This course will give you the skills and knowledge you need to succeed in business analytics, helping you stay ahead of the curve in a rapidly changing landscape.2 | Skills Gained - Master Data Analysis, Statistical Modeling, and Business Analytics In this course, you'll gain a deep understanding of data analysis, statistical modeling, and business analytics. You'll learn how to use Excel to perform data analytics, how to apply regression analysis and hypothesis testing, and how to make informed decisions based on your data analysis.3 | Case Studies and Practice Activities - Apply Your Skills to Real-World Problems One of the best ways to learn is by doing, and this course includes a range of case studies and practice activities to help you apply your skills to real-world problems. Whether you're working through a case study or practicing data analysis in Excel, you'll have the chance to put your newfound skills into action.4 | Q&A Support and Instructor Engagement - Get the Help You Need When You Need ItLearning can be challenging, but you don't have to go it alone. The Q&A and student communities are great places to get help and connect with others. I am also available to answer any questions you have and provide support as you progress through the course.In conclusion, "Statistics for Business Analytics: Data Analysis with Excel" is the perfect course for anyone looking to build their skills and advance their career in business analytics. With its comprehensive curriculum, practical case studies, and supportive community, you'll gain the skills and confidence you need to succeed in today's data-driven business world.Don't miss out on this opportunity to transform your career. Enroll in "Statistics for Business Analytics: Data Analysis with Excel" today and start your journey to becoming a data analysis expert.

Overview
Section 1: Introduction

Lecture 1 Introduction

Lecture 2 IMPORTANT: Download Course Material

Lecture 3 CASE STUDY - Statistics in the FAANG Companies

Section 2: Introduction to Statistics

Lecture 4 Game Plan for Introduction to Statistics

Lecture 5 Types of Variables

Lecture 6 Population vs Sample

Lecture 7 Case Study Briefing

Lecture 8 Measures of Central Tendency

Lecture 9 Mean

Lecture 10 EXCEL: Mean

Lecture 11 Median

Lecture 12 EXCEL: Median

Lecture 13 Mode

Lecture 14 EXCEL: Mode

Lecture 15 CHALLENGE: EXCEL - Central Tendency

Lecture 16 Standard Deviation

Lecture 17 EXCEL: Standard Deviation

Lecture 18 Coefficient of Variation

Lecture 19 EXCEL: Coefficient of Variation

Lecture 20 Normal Distribution

Lecture 21 EXCEL: Normal Distribution

Lecture 22 Covariance

Lecture 23 EXCEL: Covariance

Lecture 24 Correlation

Lecture 25 EXCEL: Correlation

Section 3: Confidence Intervals

Lecture 26 Game Plan for Confidence Intervals

Lecture 27 Case Study Briefing

Lecture 28 Standard Error of the Sample Mean

Lecture 29 EXCEL: Standard Error of the Sample Mean

Lecture 30 Z-score and Standardization

Lecture 31 EXCEL: Z-score and Standadization

Lecture 32 Confidence Level

Lecture 33 EXCEL: Confidence Level

Lecture 34 Confidence Interval with Large Samples

Lecture 35 EXCEL: Confidence Interval with Large Samples

Lecture 36 CASE STUDY: Guinness Beer and the T-student distribution

Lecture 37 T-Student Distribution

Lecture 38 Confidence Interval with Small Samples

Lecture 39 EXCEL: Confidence Interval with Small Samples

Lecture 40 Your feedback is valuable

Section 4: Hypothesis Testing

Lecture 41 Game Plan for Hypothesis Testing

Lecture 42 CASE STUDY: Improving Amazon Fashion Product Returns using Business Analytics

Lecture 43 What is Hypothesis Testing?

Lecture 44 P-value

Lecture 45 Type I and Type II errors

Lecture 46 CASE STUDY: Publication Bias in Statistics

Lecture 47 How to test your hypothesis? (Known Variance and 2-Tails)

Lecture 48 CASE STUDY BRIEFING: Tesla Production

Lecture 49 EXCEL: How to test your hypothesis (known Variance and 2-Tails)

Lecture 50 How to test your hypothesis? (unknown Variance and 2-Tails)

Lecture 51 EXCEL: How to test your hypothesis (known Variance and 2-Tails)

Lecture 52 Paired T-Test (2-Tails)

Lecture 53 Excel: Paired T-Test (2-Tails

Lecture 54 Two Sample T-Test (2-Tails)

Lecture 55 Excel: Two Sample T-Test (2-Tails)

Lecture 56 One-tailed tests

Lecture 57 EXCEL: One-tailed tests part 1

Lecture 58 EXCEL: One tailed tests part 2

Section 5: Regression Analysis

Lecture 59 Game Plan for Regression Analysis

Lecture 60 CASE STUDY BRIEFING: Pricing Diamonds

Lecture 61 Linear Regression

Lecture 62 EXCEL: Scatterplot

Lecture 63 EXCEL: Linear Regression

Lecture 64 Linear Regression Statistics and Output

Lecture 65 EXCEL: Linear Regression Statistics and Output

Lecture 66 Dummy Variable Trap

Lecture 67 EXCEL: Linear Regression with Dummy Variables

Lecture 68 CASE STUDY: Linearity Bias in Statistics and Business Analytics

Lecture 69 Multilinear Regression

Lecture 70 EXCEL: Multilinear Regression

Lecture 71 Under and Overfitting

Lecture 72 Training and Test Set

Lecture 73 EXCEL: Training and Test Set

Lecture 74 EXCEL: Predictions

Lecture 75 Assessing Regression Models

Lecture 76 EXCEL: Assessing Regression Model

Lecture 77 STATISTICS CASE STUDY: Dangers of Regression Analysis

Section 6: Bonus Section

Lecture 78 Bonus Lecture

Aspiring data analysts who are interested in developing their expertise in statistics and business analytics,Business professionals who want to develop their data analysis skills to make informed business decisions,Entrepreneurs and small business owners who want to use data analysis to make informed business decisions and grow their businesses,IT professionals who want to develop their skills in data analysis and data modeling to advance their careers,Managers and executives who want to understand the role of data analytics in decision making and lead their teams in data-driven decision making

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