Dr. David C. Juran, who teaches courses in statistics for management and managing operations, is a winner of six teaching awards at Columbia Business School and at the Cornell Johnson Graduate School of Management, including the EMBA Globe Award for Teaching Excellence. Juran’s research has appeared in Management Science, Journal of Operations Management, and other journals. Juran’s academic interests are informed by extensive industrial and corporate experience at Pepperidge Farm, Spaulding Company, and Juran Institute, as well as his experience as an independent management consultant for organizations such as [x+1], Gordian Group, Johnson & Johnson, MarketBridge, MTV Networks, Opera Solutions, Veeco, and Carl Zeiss. Dr. Juran earned his Ph.D. at Cornell University’s Johnson Graduate School of Management, concentrating in the fields of operations management, operations research, and organizational behavior.
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Overview and Courses
In a world where data is key to business operations and decision making, understanding how to collect the right data and provide precise and clear insights to your teams and stakeholders is crucial.
In this certificate program, you will turn data into actionable information to make better business decisions. You’ll uncover the patterns and trends hidden within various types of data so that you can effectively share these insights with stakeholders. You'll learn to determine the best ways to represent different data types while discovering how to apply probability principles through modeling, sampling, and regression analysis.
The fundamental analytical skills you gain will not only substantiate your business choices but also enable you to predict future outcomes and opportunities for your business.
You will have six months to complete the required elements for this certificate program, but this flexible approach allows you to finish sooner based on your schedule.
Much of business involves translating data into insights that others can grasp and act on. To do this effectively, you need to excel in the art of presenting data-based insights in a clear, accessible way.
In this course, you will build a solid foundation in basic statistical concepts. You’ll discover how to model unpredictable events and incorporate them into your decision-making processes. You’ll also interpret the importance of random events. Finally, you’ll develop effective graphs and learn to model a decision or process, helping you make sound decisions for your teams.
In a business environment, the main objective of gathering information is to harness it for decision making. By integrating data with statistical and probabilistic principles, you can make decisions that have a higher likelihood of yielding desired outcomes for your team and your organization as a whole.
In this course, you will develop skills in decision analysis. You’ll construct a decision tree, a process that also aids in determining the extent of effort required to collect information. In processes like these, some calculations may be carried out manually, while others can be streamlined with the use of spreadsheet software. You’ll be guided through both types of solutions, enabling you to select the right tool for each task in your future projects.
When aiming to construct a model, the goal is to strike a balance among accuracy, ease of use, and audience comprehension. Interestingly, numerous phenomena in both the natural and business worlds can be captured using the renowned bell curve. Harnessing the power of the bell curve will set you up for success in your business forecasting efforts.
In this course, you will employ the normal distribution as a new tool to generate more effective forecasts. You’ll identify cause-and-effect relationships that are relevant to your business decisions. You’ll also discover how to recognize when the accuracy of this tool falls short of expectations and employ corrective adjustments accordingly.
By the end of this course, you will have the necessary skills to apply normal distributions when forecasting for your business.
Businesses rely heavily on data to make informed decisions, yet data collection comes with its own costs. To optimize this process, it’s key to assess how much data you truly need to gather to make precise decisions.
In this course, you will apply the science of sampling, using data from a sample of a population to draw conclusions about the entire population. You’ll identify the appropriate sampling method for a particular scenario and business goal. Once you have this data, you’ll utilize it to predict outcome probabilities with improved accuracy. Finally, you’ll explore the reverse process: understanding how much data collection is required from a set accuracy goal.
Both these methodologies hold substantial value in business planning and will set you up for a more optimized approach to data collection for your business.
Basic statistical tools provide a starting point, but when it comes to tackling complex business scenarios, you often need more. Making informed decisions frequently requires the ability to devise and test hypotheses.
In this course, you will practice creating and testing hypotheses. You’ll examine how to construct a hypothesis that is rigorous and testable then test your hypotheses using different types of statistical data. Combining this skillset with your foundations in statistics and probability, you’ll enhance your understanding of potential outcomes.
By the end of this course, you will be equipped with the skills necessary to back up business decisions with solid mathematical justification and foster improved communication about your decisions with stakeholders.
By integrating several tools and concepts in applied statistics, you are now ready to make even more precise future predictions. The process of fitting these tools into a model that represents your data accurately is known as regression. Despite the term “simple regression model,” it can prove to be a formidable tool in business decision making.
In this course, you will practice working with regression models. You’ll discover how to construct a linear model of the relationship between two variables. You’ll also use a simple regression model to calculate statistics of interest for your business question or hypothesis.
Finally, you will make predictions about the future behavior of a system based on the regression model. Since a multitude of situations can be accurately explained and predicted using this type of model, this skillset will set you up for success in your future business analysis efforts.
A simple regression predicts outcomes based on the correlation between two variables; in the real world, however, most decisions are far more complex, often influenced by numerous factors. Multiple regression allows you to consider these additional factors when making decisions. By building on the foundational techniques, you can create a model that more accurately reflects reality, thus enhancing the confidence in your managerial decisions.
In this course, you will discover how to improve a predictive model by incorporating more variables and use a variety of statistical tools to verify the validity of your model. Since there might be situations where your system doesn’t perfectly fit as you factor in more variables, you’ll also examine how to identify such scenarios and compensate for them when constructing your predictive model.
As you introduce multiple regression analysis into your skillset, you will gain a more comprehensive approach to the decision-making process, helping you overcome challenges in your business.
eCornell’s online Workshops are live, interactive 3-hour learning experiences led by Cornell faculty experts. These premium short-format sessions focus on AI topics and are designed for busy professionals who want to gain immediately applicable skills and strategic perspectives. Workshops include faculty presentations, breakout discussions, guided hands-on practice, and downloadable resources.
The AI Workshops All-Access Pass provides you with unlimited participation for 6 months from your date of purchase. Whether you choose to attend one workshop per month or several per week, the All-Access Pass will allow you to customize your AI journey and stay on top of the latest AI trends.
Workshops cover a range of cutting-edge AI topics applicable across industries, hosted by Cornell faculty at the forefront of their fields. Whether you are just getting started with AI, seeking to build your AI skillset, or exploring advanced applications of AI, Workshops will provide you with an action-oriented learning experience for immediate application in your career. Sample Workshops include:
- Work Smarter with AI Agents: Individual and Team Effectiveness
- Leading AI Transformation: Bigger Than You Imagine, Harder Than You Expect
- Using AI at Work: Practical Choices and Better Results
- Search and Discoverability in the Era of AI
- Don’t Just Prompt AI – Govern it
- AI-Powered Product Manager
- Leverage AI and Human Connection to Lead Through Uncertainty
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How It Works
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Key Course Takeaways
- Determine how to represent different types of data and apply the rules of probability to analyzing that data
- Analyze data and probabilities to make informed business decisions to achieve desired outcomes
- Apply the “bell curve” model to various phenomena to make more accurate probability predictions in a scenario
- Understand the decision-making environment through the application of statistical sampling
- Use statistical methods to determine the truth or falsehood of a statement
- Examine the relationship between variables to better predict the future behavior of a system
- Consider multiple variables when predicting the behavior of a complex system



What You'll Earn
- Applied Statistics Certificate from Cornell’s SC Johnson College of Business
- 70 Professional Development Hours (7 CEUs)
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Who Should Enroll
- Business and marketing analysts who turn data into strategic insights
- Financial and risk professionals/analysts who use statistics for investment decisions
- Management and strategy leaders who drive data-informed business outcomes
- Sales and operations specialists who optimize processes using analytics
- Emerging data careers including pre-MBA and/or entry-level roles in data science and business intelligence
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$3,750
Applied Statistics
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