Essential Statistics for Data Analysis using Excel from edX

If you’re considering a career as a data analyst, you need to know about histograms, Pareto charts, Boxplots, Bayes’ theorem, and much more. In this applied statistics course, the second in our Microsoft Excel Data Analyst XSeries, use the powerful tools built into Excel, and explore the core principles of statistics and basic probability—from both the conceptual and applied perspectives. Learn about descriptive statistics, basic probability, random variables, sampling and confidence intervals, and hypothesis testing. And see how to apply these concepts and principles using the environment, functions, and visualizations of Excel.

As a data science pro, the ability to analyze data helps you to make better decisions, and a solid foundation in statistics and basic probability helps you to better understand your data. Using real-world concepts applicable to many industries, including medical, business, sports, insurance, and much more, learn from leading experts why Excel is one of the top tools for data analysis and how its built-in features make Excel a great way to learn essential skills.

Before taking this course, you should be familiar with organizing and summarizing data using Excel analytic tools, such as tables, pivot tables, and pivot charts. You should also be comfortable (or willing to try) creating complex formulas and visualizations. Want to start with the basics? Check out DAT205x: Introduction to Data Analysis using Excel. As you learn these concepts and get more experience with this powerful tool that can be extremely helpful in your journey as a data analyst or data scientist, you may want to also take the third course in our series, DAT206x Analyzing and Visualizing Data with Excel. This course includes excerpts from Microsoft Excel 2016: Data Analysis and Business Modeling from Microsoft Press and authored by course instructor Wayne Winston.

edX offers financial assistance for learners who want to earn Verified Certificates but who may not be able to pay the fee. To apply for financial assistance, enroll in the course, then follow this link to complete an application for assistance.

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Examines tools standard in several industries

Develops core skills for data analysts and scientists

Taught by experts recognized for their work in the field

Explores real-world concepts from various fields

Requires familiarity with Excel and complex formulas

Includes excerpts from a Microsoft Press book

Reviews summary

Comprehensive statistics for data analysis in excel

This course provides a comprehensive overview of essential statistics concepts, using Microsoft Excel as a tool for data analysis. While it is recommended to have some prior experience with Excel's analytic tools, it is also suitable for beginners who are willing to put in the effort to learn more complex formulas and visualizations.

Uses real-world concepts and examples.

"Using real-world concepts applicable to many industries, including medical, business, sports, insurance, and much more, ..."

Some prior knowledge of Excel's analytic tools is recommended.

"Before taking this course, you should be familiar with organizing and summarizing data using Excel analytic tools, such as tables, pivot tables, and pivot charts."

Covers a wide range of statistical concepts in depth.

"Don't get fooled by the title of this course - it says Essential Statistics yet it is a very comprehensive and challenging course if you are not coming from a serious statistical background."

Course modules may change without prior warning.

"Course modules changed halfway without prior warning, so you're not certain that you will actually finish the modules that you had chosen when you started."

Certificates are relatively expensive.

"Certificates are relatively expensive for the content that is provided."

Career center

Learners who complete Essential Statistics for Data Analysis using Excel will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts analyze raw data to identify trends, patterns, and outliers. They interpret and communicate their findings to stakeholders to support decision-making. This course helps build a foundation in essential statistics and probability, which is essential for Data Analysts to understand and analyze data effectively. By learning about descriptive statistics, sampling techniques, and hypothesis testing, learners can develop the skills needed to draw meaningful conclusions from data and make informed decisions.

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Business Analyst

Business Analysts help organizations improve their performance by identifying and solving business problems. They use data analysis to understand the current state of a business and to develop and implement solutions. This course provides a strong foundation in statistics and probability, which is essential for Business Analysts to understand and analyze data effectively. By learning about sampling techniques, hypothesis testing, and regression analysis, learners can develop the skills needed to make data-driven recommendations that improve business outcomes.

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Data Scientist

Data Scientists use data analysis and machine learning to solve complex business problems. They develop and implement predictive models and algorithms to uncover insights and make predictions. This course provides a strong foundation in essential statistics and probability, which is essential for Data Scientists to understand and analyze data effectively. By learning about descriptive statistics, sampling techniques, and regression analysis, learners can develop the skills needed to build and evaluate predictive models that help businesses make better decisions.

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Statistician

Statisticians design and conduct surveys and experiments to collect and analyze data. They use statistical methods to draw conclusions about the population from which the data was collected. This course provides a strong foundation in essential statistics and probability, which is essential for Statisticians to design and conduct valid and reliable studies. By learning about sampling techniques, hypothesis testing, and regression analysis, learners can develop the skills needed to collect and analyze data effectively and make informed conclusions.

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Market Research Analyst

Market Research Analysts conduct research to understand consumer behavior and trends. They use data analysis to identify and target potential customers and to develop marketing strategies. This course provides a strong foundation in essential statistics and probability, which is essential for Market Research Analysts to understand and analyze data effectively. By learning about descriptive statistics, sampling techniques, and regression analysis, learners can develop the skills needed to design and conduct market research studies and make informed recommendations.

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Financial Analyst

Financial Analysts use data analysis to evaluate the financial performance of companies and to make investment recommendations. They use statistical methods to assess risk and return and to develop investment strategies. This course provides a strong foundation in essential statistics and probability, which is essential for Financial Analysts to understand and analyze financial data effectively. By learning about descriptive statistics, sampling techniques, and regression analysis, learners can develop the skills needed to build and evaluate financial models and make informed investment recommendations.

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Epidemiologist

Epidemiologists investigate the causes and spread of diseases. They use data analysis to identify risk factors and to develop prevention strategies. This course provides a strong foundation in essential statistics and probability, which is essential for Epidemiologists to understand and analyze data effectively. By learning about descriptive statistics, sampling techniques, and regression analysis, learners can develop the skills needed to design and conduct epidemiological studies and make informed recommendations.

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Biostatistician

Biostatisticians use statistical methods to design and analyze studies in the field of biology and medicine. They develop and implement statistical models to understand the causes and effects of diseases and to develop new treatments. This course provides a strong foundation in essential statistics and probability, which is essential for Biostatisticians to understand and analyze data effectively. By learning about descriptive statistics, sampling techniques, and regression analysis, learners can develop the skills needed to design and conduct biomedical studies and make informed conclusions.

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Actuary

Actuaries use statistical methods to assess risk and uncertainty. They develop and implement models to calculate the probability of future events and to determine the appropriate insurance premiums. This course provides a strong foundation in essential statistics and probability, which is essential for Actuaries to understand and analyze data effectively. By learning about descriptive statistics, sampling techniques, and regression analysis, learners can develop the skills needed to build and evaluate actuarial models and make informed recommendations.

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Economist

Economists analyze data to understand the behavior of the economy. They use statistical methods to forecast economic trends and to develop economic policies. This course provides a strong foundation in essential statistics and probability, which is essential for Economists to understand and analyze data effectively. By learning about descriptive statistics, sampling techniques, and regression analysis, learners can develop the skills needed to build and evaluate economic models and make informed recommendations.

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Operations Research Analyst

Operations Research Analysts use mathematical and statistical methods to solve complex problems in business and industry. They develop and implement models to optimize supply chains, improve production processes, and reduce costs. This course provides a strong foundation in essential statistics and probability, which is essential for Operations Research Analysts to understand and analyze data effectively. By learning about descriptive statistics, sampling techniques, and regression analysis, learners can develop the skills needed to build and evaluate operations research models and make informed recommendations.

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Quality Assurance Manager

Quality Assurance Managers ensure that products and services meet quality standards. They use data analysis to identify and correct quality problems. This course provides a strong foundation in essential statistics and probability, which is essential for Quality Assurance Managers to understand and analyze data effectively. By learning about descriptive statistics, sampling techniques, and regression analysis, learners can develop the skills needed to design and implement quality assurance programs and make informed decisions.

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Risk Manager

Risk Managers identify and assess risks to an organization. They develop and implement strategies to mitigate risks and protect the organization from losses. This course provides a strong foundation in essential statistics and probability, which is essential for Risk Managers to understand and analyze data effectively. By learning about descriptive statistics, sampling techniques, and regression analysis, learners can develop the skills needed to build and evaluate risk management models and make informed recommendations.

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Data Engineer

Data Engineers design and build the infrastructure that stores and processes data. They use statistical methods to optimize data storage and retrieval. This course provides a strong foundation in essential statistics and probability, which is essential for Data Engineers to understand and analyze data effectively. By learning about descriptive statistics, sampling techniques, and regression analysis, learners can develop the skills needed to design and implement data engineering solutions and make informed recommendations.

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Machine Learning Engineer

Machine Learning Engineers design and build machine learning models. They use statistical methods to train and evaluate machine learning models. This course provides a strong foundation in essential statistics and probability, which is essential for Machine Learning Engineers to understand and analyze data effectively. By learning about descriptive statistics, sampling techniques, and regression analysis, learners can develop the skills needed to build and evaluate machine learning models and make informed recommendations.

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Essential Statistics for Data Analysis using Excel

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