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  3. Advanced Quantitative Statistics with Excel

Advanced Quantitative Statistics with Excel

This course on Advanced Quantitative Statistics with Excel equips learners with skills in hypothesis testing and regression analysis, using Excel's Analysis ToolPak to analyze real-world data, solve business problems, and drive informed decisions.

Diogo Resende
Diogo Resende
Business | core | 1 hour |   Published: Aug 2024
In partnership with:  Coursera

    Discussions

Overview

1KSTUDENTS*
97.8%RECOMMEND*

This course includes:

  • 1 hours of on-demand video  
  • Certificate of completion  
  • Direct access/chat with the instructor 
  • 100% self-paced online 
This comprehensive course is tailored specifically for data analysts, business professionals, and anyone looking to significantly enhance their proficiency in Microsoft Excel for complex data analysis tasks. By exploring a wide range of advanced Excel features and techniques, participants will gain the ability to analyze and interpret data to make informed business decisions. Learners will be introduced to real-world applications, using Excel to tackle diverse scenarios. The main case study will focus on Marketing, specifically the pricing of diamonds based on their characteristics and analyzing production quality data in manufacturing. By the end of the case study, learners will feel empowered to apply regression analysis to problems in their own field. This practical approach ensures that learners will leave the course equipped to handle complex data analysis challenges, providing them with the skills to conduct hypothesis testing, regression analysis, and more. By the end of this course, learners will have mastered the necessary tools to effectively visualize, analyze, and interpret data using Excel, making them invaluable assets in their professional fields. This course will empower participants to transform raw data into compelling insights, driving business strategies and achieving better outcomes. 

Skills You Will Gain

Data Analysis
Excel
Hypothesis Testing
Statistics

Learning Outcomes (At the end of this program you will be able to)

  • Practice with Excel’s Analysis ToolPak to perform advanced statistical analysis.
  • Evaluate various hypothesis tests within Excel, including t-tests and ANOVA.
  • Analyze business problems with the use of Excel to conduct simple and multiple regression analyses

Prerequisites

Basic proficiency in Microsoft Excel is required, along with an understanding of basic statistical concepts such as measures of central tendency, dispersion, and confidence intervals. These foundational skills will help learners grasp more advanced data analysis techniques in the course.

Who Should Attend

The course is designed for Business Analysts and Data Analysts seeking to enhance their analytical skills and improve their decision-making capabilities. It is ideal for professionals who regularly handle data, generate reports, and provide insights to support business strategies. Participants are expected to have a keen interest in leveraging data to drive organizational success and be open to learning advanced analytical techniques and tools.

Curriculum

Instructors

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*Where courses have been offered multiple times, the “# Students” includes all students who have enrolled. The “%Recommended” shown is also based on this data.
1Module 1: Introduction to Hypothesis Testing
2 Module 2: Advanced Hypothesis Testing Techniques
3Module 3: Regression Analysis in Excel
Diogo Resende

Diogo Resende

With a profound commitment to bridging analytical acumen with practical business solutions, Diogo brings a wealth of experience from both the corporate arena and academia. Holding a Master’s Degree in Management from ESMT Berlin, his academic journey delved deeply into analytics, culminating in a thesis that addressed the complex challenge of mitigating demand and supply disparities exacerbated by weather conditions.

Complementing his academic achievements, Diogo actively contributed to real-world initiatives, including supporting the United Nations Development Program in enhancing financial inclusion through mobile money in Ethiopia and Lesotho. This blend of theoretical rigor and hands-on engagement defines his teaching approach—one that equips learners not only with conceptual understanding but also with actionable insights derived from diverse global contexts.

Diogo’s academic foundation is further enriched by a robust professional background. As a Senior Commercial Planning and Strategy Manager at Zalando Germany, he led key initiatives aimed at driving commercial performance, working closely with cross-functional teams to execute strategic plans. His influence extends beyond traditional business settings into the digital learning space, where he has created six highly acclaimed Business Analytics courses on platforms like Udemy. With over 4,000 students enrolled and each course earning bestseller status, his dedication to knowledge-sharing continues to impact learners around the world.

Outside of his corporate and academic contributions, Diogo has pursued a wide range of impactful roles—from serving as a Pro Bono Consultant for the Lesotho Scaling Inclusion through Mobile Money platform to working as an Editor and Marketing Associate at Rádio Universidade de Coimbra. Whether developing sustainable business plans or anchoring news segments, his multifaceted journey reflects a consistent passion for innovation, collaboration, and positive change.

As he steps into his role as an educator, Diogo is committed to not only imparting knowledge but also cultivating a vibrant, inquisitive community of learners united by a shared pursuit of transformative insight.

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Segment 01: Introduction to the Course & Meet Your Instructor

Segment 02: Basics of Hypothesis Testing

Segment 03: Understanding P-Values and Statistical Significance

Segment 04: T-tests for Known Variance

Segment 05: Conducting a Simple T-Test in Excel

Segment 12: Introduction to Regression Analysis

Segment 13: Conducting Linear Regression in Excel

Segment 14: Exploring Multiple Regression Analysis

Segment 15: Conducting Multi -Linear Regression in Excel

Segment 16: Congratulations and Continuous Learning Journey

Segment 06: Understanding One-Tailed Tests

Segment 07: Performing a One-Tailed Test in Excel w Video

Segment 08: Understanding the Two-Sample T-Test

Segment 09: Performing a Two-Sample T-Test in Excel

Segment 10: Introduction to ANOVA

Segment 11: Conducting ANOVA in Excel