Statistical Analysis Fundamentals using Excel from Coursera

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.

What's inside

Syllabus

Introduction and Descriptive Statistics

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.

Data Visualization

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.

Introduction to Probability Distributions

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.

Regression Analysis and Forecasting

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.

Analysing Sales Performance and Forecasting

The project focuses on analysing sales performance using data visualization and making simple forecasts for future sales based on historical data.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Introduces data visualization, a core skill in business intelligence and data analytics

Covers probability distributions and hypothesis testing, using examples to illustrate concepts

Develops regression analysis skills, applicable to examining variable relationships and making predictions

Applies fundamental concepts of statistics to real-world scenarios

Provides an opportunity to apply concepts to a real-life scenario through a hands-on project

Suitable for professionals and students aiming for a career in BI or data analytics

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Statistical Analysis Fundamentals using Excel with these activities:

Attend a Data Analytics Meetup

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Provides opportunities to connect with professionals in the field.

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Find a local data analytics meetup.
Attend the meetup.
Network with other attendees.

Practice Using Microsoft Excel for Data Analysis

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Refreshes Excel skills necessary for completing the course project.

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Open a spreadsheet and enter some data.
Use Excel formulas and functions to analyze the data.

Mentor a Peer in Descriptive Statistics

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Solidifies understanding of descriptive statistics through teaching.

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Find a peer who needs help with descriptive statistics.
Review the concepts with your peer.
Answer their questions and provide guidance.

Six other activities

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Review Descriptive Statistics

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Refreshes knowledge of descriptive statistics concepts covered in module 1.

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Review notes or textbook chapters on descriptive statistics.
Take a practice quiz or work through practice problems.

Learn about Data Visualization Best Practices

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Reinforces understanding of data visualization principles covered in module 2.

Browse courses on Data Visualization Best Practices

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Find tutorials or articles on data visualization best practices.
Follow the steps outlined in the tutorials to create visualizations.
Review the visualizations and identify areas for improvement based on best practices.

Probability Distribution Practice Problems

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Provides additional practice with probability distribution concepts covered in module 3.

Browse courses on Probability Distributions

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Find practice problems or online quizzes on probability distribution.
Solve the problems or take the quizzes.
Review the solutions and identify areas for improvement.

Create a Data Visualization Tutorial for Beginners

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Deepens understanding of data visualization through teaching.

Browse courses on Data Visualization

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Choose a data visualization topic to cover.
Create a tutorial outlining the steps involved in creating a visualization.
Share your tutorial with others.

Build a Regression Model for Sales Forecasting

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Applies regression analysis techniques covered in module 4 to a real-world sales forecasting scenario.

Browse courses on Regression Analysis

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Gather historical sales data.
Build a regression model using the data.
Evaluate the model and make predictions.
Write a report summarizing the results.

Compile a List of Resources for Statistical Analysis

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Provides a valuable resource for future reference.

Browse courses on Statistical Analysis

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Search for online resources related to statistical analysis.
Compile a list of the most useful resources.
Share your list with others.

Career center

Learners who complete Statistical Analysis Fundamentals using Excel will develop knowledge and skills that may be useful to these careers:

Data Analyst

A Data Analyst plays an integral role in a business as they are responsible for analyzing data, interpreting it, and presenting the findings to key stakeholders. They transform raw data into actionable insights that drive informed decision-making. This course, Statistical Analysis Fundamentals using Excel, provides a strong foundation for individuals aspiring to become Data Analysts. It equips learners with essential statistical analysis skills, data visualization techniques, and regression analysis methods, enabling them to extract meaningful insights from data and communicate them effectively.

See salaries and explore the career path for Data Analyst

Business Analyst

Business Analysts are responsible for analyzing business processes, identifying areas for improvement, and recommending solutions to optimize performance. They leverage data analysis and statistical techniques to understand business needs, develop strategies, and evaluate outcomes. This course provides Business Analysts with a comprehensive understanding of statistical concepts, data visualization methods, and regression analysis techniques, enabling them to make data-driven decisions and drive business growth.

See salaries and explore the career path for Business Analyst

Data Scientist

Data Scientists combine expertise in statistics, programming, and data mining to extract valuable insights from large and complex datasets. They develop predictive models, analyze trends, and build solutions to solve real-world business problems. This course provides Data Scientists with a solid foundation in statistical analysis, data visualization, and regression techniques, equipping them with the skills necessary to drive data-driven decision-making and innovation.

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Operations Research Analyst

Operations Research Analysts use mathematical and statistical models to optimize business operations and decision-making. They analyze data, identify patterns, and develop solutions to improve efficiency, reduce costs, and increase profitability. This course provides Operations Research Analysts with a strong foundation in statistical analysis, data visualization, and regression techniques, enabling them to make data-driven decisions and drive operational excellence.

See salaries and explore the career path for Operations Research Analyst

Quantitative Analyst

Quantitative Analysts apply mathematical and statistical methods to analyze financial data and assess investment opportunities. They develop models to forecast market trends, evaluate risk, and make investment recommendations. This course provides Quantitative Analysts with a strong foundation in statistical analysis, probability distributions, and regression techniques, enabling them to make data-driven decisions and drive investment performance.

See salaries and explore the career path for Quantitative Analyst

Market Research Analyst

Market Research Analysts collect, analyze, and interpret data to understand market trends, customer behavior, and industry dynamics. They provide insights that help businesses make informed decisions about product development, marketing campaigns, and target audience identification. This course provides Market Research Analysts with a strong foundation in statistical analysis, data visualization, and regression techniques, enabling them to extract meaningful insights from market data and drive business growth.

See salaries and explore the career path for Market Research Analyst

Financial Analyst

Financial Analysts evaluate financial data, including income statements, balance sheets, and cash flow statements, to assess the financial health and performance of companies. They develop financial models, analyze trends, and make recommendations to support investment decisions. This course provides Financial Analysts with a strong foundation in statistical analysis, probability distributions, and regression techniques, enabling them to make data-driven decisions and drive investment performance.

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Statistician

Statisticians design, conduct, and analyze statistical surveys and experiments. They collect, analyze, interpret, and present data to provide insights into a wide range of topics, such as public health, education, and manufacturing. This course provides Statisticians with a strong foundation in statistical analysis, data visualization, and regression techniques, enabling them to design and execute statistical studies and communicate their findings effectively.

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Actuary

Actuaries use mathematical and statistical techniques to assess risk and uncertainty, particularly in the insurance and financial sectors. They develop models to predict future events, such as mortality rates and investment returns, and use these predictions to calculate insurance premiums and make investment decisions. This course provides Actuaries with a strong foundation in statistical analysis, probability distributions, and regression techniques, enabling them to make data-driven decisions and manage risk effectively.

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Risk Manager

Risk Managers identify, assess, and mitigate risks that may impact an organization's operations, finances, and reputation. They develop strategies to manage risks and ensure business continuity. This course provides Risk Managers with a strong foundation in statistical analysis, probability distributions, and regression techniques, enabling them to make data-driven decisions and manage risk effectively.

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Credit Analyst

Credit Analysts assess the creditworthiness of individuals and businesses to determine their ability to repay loans. They analyze financial data, including income statements, balance sheets, and cash flow statements, to make lending decisions. This course provides Credit Analysts with a strong foundation in statistical analysis, probability distributions, and regression techniques, enabling them to make data-driven decisions and manage risk effectively.

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Data Engineer

Data Engineers design, build, and maintain the infrastructure that stores and manages data. They develop data pipelines, create data models, and ensure the quality and integrity of data. This course may be helpful for Data Engineers who wish to expand their knowledge of statistical analysis and data visualization techniques, which can be beneficial for understanding data characteristics and developing data-driven solutions.

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Software Engineer

Software Engineers design, develop, and maintain software applications. They use a variety of programming languages and tools to create software that meets the needs of users. This course may be helpful for Software Engineers who wish to develop software solutions that leverage statistical analysis and data visualization techniques to provide insights and drive decision-making.

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Data Architect

Data Architects design and manage the architecture of data systems, including databases, data warehouses, and data lakes. They ensure that data is stored, managed, and accessed in a way that meets the needs of the organization. This course may be helpful for Data Architects who wish to expand their knowledge of statistical analysis and data visualization techniques, which can be beneficial for understanding data requirements and designing data-driven solutions.

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Database Administrator

Database Administrators manage and maintain databases, ensuring their performance, security, and integrity. They work with database systems to create, modify, and optimize databases to meet the needs of users. This course may be helpful for Database Administrators who wish to develop data analysis and data visualization skills, which can be beneficial for understanding data characteristics and optimizing database performance.

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