Statistical Analysis Fundamentals using Excel
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Statistical Analysis Fundamentals using Excel
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What you'll learn
Describe the fundamental concepts of statistics and apply them to business and data analytics settings.
Apply data collection, analysis, and interpretation techniques to derive actionable insights for making informed business decisions.
Apply descriptive and inferential analysis methods to derive insights and actionable recommendations from data.
Apply hypothesis testing, regression analysis, and forecasting to support business decision-making processes.
Skills you'll gain
- Statistical Methods
- Predictive Modeling
- Statistical Visualization
- Forecasting
- Probability & Statistics
- Data Visualization Software
- Data Presentation
- Statistical Hypothesis Testing
- Statistics
- Business Analytics
- Predictive Analytics
- Data Analysis
- Statistical Analysis
- Descriptive Analytics
- Spreadsheet Software
- Probability Distribution
- Data Visualization
- Descriptive Statistics
- Regression Analysis
Tools you'll learn
Details to know
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There are 5 modules in this course
This course is aimed at familiarizing Data and Business professionals with the basic concepts of statistical analysis and methods used for data-driven decision-making.
After completing this course, you will be able to apply descriptive and inferential analysis methods, use data visualization methods to communicate data, apply concepts of probability in real-life scenarios, and apply regression techniques to predict trends. The course takes a hands-on approach to statistical analysis using Microsoft Excel and uses examples to illustrate the concepts to help you gain the foundational knowledge of statistical techniques needed to solve business intelligence (BI) problems. A hands-on project will provide you an opportunity to apply the concepts to a real-life scenario involving data-driven decision-making and an understanding of basic statistical thinking and reasoning. This course is suitable for professionals or students who aspire to embark on a career in the BI or Data Analytics fields by equipping them with the crucial skills and knowledge in statistical analysis. It is expected that learners be familiar with Excel/spreadsheet basics and high school mathematics prior to starting this course.
This module introduces descriptive statistics and its role in summarizing and describing data. You will learn about the significance of statistics in making informed decisions and its relevance to professions like Data Analyst, BI Analyst, and Data Scientist. The module covers key measures of central tendency, including mean, median, and mode, and their applications in different scenarios. Additionally, you will evaluate the importance of measures of dispersion, such as variance and standard deviation, in assessing data variability.
What's included
5 videos4 readings2 assignments4 plugins
5 videos•Total 25 minutes
- Course Introduction•5 minutes
- Welcome to Statistics!•4 minutes
- Types of Data•6 minutes
- Measure of Central Tendency•6 minutes
- Measures of Dispersion•4 minutes
4 readings•Total 19 minutes
- Course Overview•5 minutes
- Helpful Tips for Course Completion•2 minutes
- Measures of Dispersion•10 minutes
- Summary and Highlights: Introduction and Descriptive Statistics•2 minutes
2 assignments•Total 36 minutes
- Practice Quiz: Introduction to Descriptive Statistics•6 minutes
- Graded Quiz: Introduction to Descriptive Statistics•30 minutes
4 plugins•Total 82 minutes
- Hands-on Lab: Getting Started with Excel Online•20 minutes
- Lab: Measure of Dispersion•30 minutes
- Lab: Descriptive Statistics•30 minutes
- Module 1 Glossary: Introduction and Descriptive Statistics•2 minutes
This module focuses on data visualization and its role in effectively communicating information. You will learn to identify different types of visualizations suitable for various types of data and information. The module covers the calculation and interpretation of measures and graphs used in data visualization. You will also apply principles and guidelines to select appropriate visualizations based on data characteristics and communication goals. Additionally, you will learn data visualization techniques to present and communicate information clearly and intuitively. The module emphasizes the analysis and evaluation of visualizations to derive insights and effectively convey the intended message.
What's included
4 videos1 reading2 assignments3 plugins
4 videos•Total 17 minutes
- Visualization Fundamentals •3 minutes
- Statistics by Groups•5 minutes
- Statistical Charts•3 minutes
- Introducing the teacher's rating data•5 minutes
1 reading•Total 2 minutes
- Summary and Highlights: Data Visualization•2 minutes
2 assignments•Total 21 minutes
- Practice Quiz: Data Visualization•6 minutes
- Graded Quiz: Data Visualization•15 minutes
3 plugins•Total 62 minutes
- Lab: Data Visualization Using Statistical Charts•30 minutes
- Lab: Data Visualization Using Pivot Chart•30 minutes
- Module 2 Glossary: Data Visualization•2 minutes
In this module, students will apply fundamental concepts of probability to real-world scenarios. They will differentiate between various probability distributions, including the normal distribution and the T-distribution, and calculate probabilities to make informed decisions. The significance of hypothesis testing, alpha levels, and p-values in statistical analysis will be explored. Students will apply probability distribution concepts and techniques to solve practical problems and analyze real-world data.
What's included
5 videos3 readings2 assignments3 plugins
5 videos•Total 27 minutes
- Random Numbers and Probability Distributions•5 minutes
- State your hypothesis•4 minutes
- Normal Distribution•5 minutes
- T-Distribution•8 minutes
- Probability of Getting a High or Low Teaching Evaluation•6 minutes
3 readings•Total 22 minutes
- Alpha (α) and P-value•10 minutes
- Standard Normal Table•10 minutes
- Summary and Highlights•2 minutes
2 assignments•Total 36 minutes
- Practice Quiz: Introduction to Probability Distribution•6 minutes
- Graded Quiz: Introduction to Probability Distribution•30 minutes
3 plugins•Total 63 minutes
- Lab: Standard Normal Distribution•30 minutes
- Lab: Probability Distribution•30 minutes
- Module 3 Glossary: Introduction to Probability Distributions•3 minutes
This module focuses on regression analysis and its significance in business analytics. You will develop a comprehensive understanding of regression analysis and its applications in examining variable relationships and making predictions. The module covers building regression models and evaluating their assumptions, diagnosing problems, and identifying potential remedies. Additionally, you will develop forecasting skills by applying regression techniques to predict future trends and outcomes, supporting informed decision-making.
What's included
8 videos1 reading2 assignments4 plugins
8 videos•Total 50 minutes
- Overview of Regression Analysis•7 minutes
- Simple Linear Regression•7 minutes
- Building and Interpreting Simple Linear Regression Models•4 minutes
- Multiple Linear Regression•5 minutes
- Building and Interpreting Multiple Linear Regression Models•9 minutes
- (Optional) Assumption and Diagnosis in Regression Analysis•6 minutes
- Forecasting with Regression•6 minutes
- Applying Regression Techniques for Forecasting•6 minutes
1 reading•Total 2 minutes
- Summary and Highlights•2 minutes
2 assignments•Total 21 minutes
- Practice Quiz: Introduction to Regression Analysis Assessments•6 minutes
- Graded Quiz: Introduction to Regression Analysis Assessments•15 minutes
4 plugins•Total 68 minutes
- Lab: Simple Linear Regression Analysis•30 minutes
- Lab: Multiple Linear Regression Analysis•30 minutes
- Reading: Difference between Simple and Multiple Linear Regression•3 minutes
- Module 4 Glossary: Regression Analysis and Forecasting•5 minutes
The project focuses on analysing sales performance using data visualization and making simple forecasts for future sales based on historical data.
What's included
3 readings1 assignment1 peer review1 app item6 plugins
3 readings•Total 5 minutes
- Instructions for the Final Exam•1 minute
- Congratulations and Next Step•2 minutes
- Team and Acknowledgments•2 minutes
1 assignment•Total 30 minutes
- Final Exam (Statistics Fundamentals Using Excel)•30 minutes
1 peer review•Total 30 minutes
- Option 2: Peer Graded - Final Project Submission and Evaluation•30 minutes
1 app item•Total 30 minutes
- Option 1: AI Graded - Final Project: Submission and Evaluation•30 minutes
6 plugins•Total 189 minutes
- Reading: About the Course Projects•2 minutes
- Reading: Practice Project Overview•60 minutes
- Lab: Practice Project Guide•60 minutes
- Final Project Overview and Tasks•60 minutes
- Reading: Final Project Submission Guidelines and Deliverables•0 minutes
- Course Glossary: Statistics Fundamentals using Excel•7 minutes
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Reviewed on Nov 11, 2024
Statistical Analysis Fundamentals using Excel is very useful and need to implement in department level.
Reviewed on Dec 2, 2024
Good course for basic understanding of Statistical Analysis using Excel
Reviewed on Nov 7, 2025
The course was challenging yet interesting. Thank you!
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