Excel Statistics: Descriptive Data Analysis
Master Excel for data analysis. Learn descriptive statistics, probability, and visualization techniques in this beginner-friendly course.
Master Excel for data analysis. Learn descriptive statistics, probability, and visualization techniques in this beginner-friendly course.
Dive into the world of data analysis with Excel in this comprehensive course. Designed for beginners, it provides a solid foundation in statistics and probability. Learn to calculate descriptive statistics, understand probability concepts, and create impactful data visualizations using Excel. Covering both discrete and continuous probability distributions, this course equips you with essential skills for data science and analytics. Perfect for those looking to enhance their Excel proficiency and statistical knowledge.
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What you'll learn
Calculate descriptive statistics including traditional and robust estimators
Understand and apply fundamental probability concepts and rules
Utilize statistical functions in Microsoft Excel for data analysis
Create and interpret various data visualizations including histograms, scatter plots, and box plots
Apply discrete and continuous probability distributions to real-world scenarios
Develop skills in data cleaning and transformation using Excel
Skills you'll gain
This course includes:
5.75 Hours PreRecorded video
15 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This course provides a comprehensive introduction to statistics and data analysis using Microsoft Excel. Students will learn fundamental concepts in descriptive statistics, probability, and both discrete and continuous probability distributions. The curriculum covers essential skills such as calculating population and sample statistics, data visualization techniques including histograms and scatter plots, and applying various probability rules. Participants will gain hands-on experience using Excel for statistical calculations and data representation, making this course ideal for beginners in data science and analytics.
WELCOME!
Module 1 · 1 Hours to complete
Descriptive Statistics and Graphical Representation of Data
Module 2 · 3 Hours to complete
Probability
Module 3 · 3 Hours to complete
Discrete Probability Distributions
Module 4 · 3 Hours to complete
Continuous Probability Distributions
Module 5 · 4 Hours to complete
Fee Structure
Instructor
Dedicated Educator in Chemical and Biological Engineering
Charlie Nuttelman earned his B.S., M.S., and Ph.D. degrees from the Department of Chemical and Biological Engineering in 1999, 2001, and 2005, respectively. He has been an instructor in the department since 2007, teaching a total of 18 different chemical and biological engineering courses that have accumulated over 20,000 student credit hours. These courses range from introductory engineering classes to advanced senior design projects, accommodating class sizes from small lab groups to large lectures with over 400 students. Among all his courses, introductory computing is his favorite, which he has taught more than 20 times. He enjoys the creativity and open-ended nature of the problems presented in this course, particularly for students who are new to programming and engineering problem-solving. Currently, Bruce teaches seven different courses on Coursera, with two more scheduled for release by the end of 2024.
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Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.