Statistics For Business Analytics: Data Analysis With Excel

[mitsumi]

Statistics For Business Analytics: Data Analysis With Excel
Published 3/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.49 GB | Duration: 5h 26m

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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