Data Literacy and Business Analytics for Business Leaders

Learn practical statistical concepts through engaging, hands-on quizzes, exercises, and case studies, designed for data literacy and business analytics for leaders.

distinguish quantitative and qualitative variables, with continuous and discrete in quantitative, and nominal and ordinal in qualitative. include age, income, square meters, eye color, and education level.

Explore a Dioguini's pizza restaurant case study to practice key statistical concepts using a one-month dataset, KPIs like price, delivery time, toppings and add-ons in Google Sheets and Excel.

Explore how the mean, or average, serves as a key performance indicator, when arithmetic mean applies, how outliers and symmetry affect interpretation, with a Google Sheets exercise.

Create histograms for delivery time and toppings KPIs, customize the bucket size, and compute the mean with the average function in Google Sheets.

Explore the median, the center of an ordered data set and the 50th percentile, and contrast it with the mean in skewed income data, where outliers pull the mean.

Create and customize a histogram of prices, compare mean and median, and conclude that the median is a more robust KPI when prices are skewed.

Identify the mode as the most common element in a data set, used for categorical variables, with elections and fashion as examples, and practice computing modes for toppings.

Learn to compute the mode for categorical variables with an index–match–countif formula, using unique values and frequency counts, and visualize crust shares with a pie chart.

Explore how standard deviation measures dispersion around the mean. Most observations fall within one standard deviation, as shown by histograms and a delivery-time example.

Compute the standard deviation of delivery time using Google Sheets' stdev, revealing a mean of 25.06 minutes and a deviation of 2.49 minutes, and connect with the normal distribution.

Explore correlation, especially Pearson correlation, as a measure of the strength between two variables, -1 to 1. Note umbrellas and rain as examples, and that correlation does not imply causation.

Learn to compute correlations in Google Sheets, create scatter plots with trend lines, and interpret price-delivery time and toppings-price relationships.

Examine the normal (Gaussian) distribution, its symmetric bell shape around the mean, and the 68-95-99.7 rule, using standard deviations to identify outliers and support Six Sigma quality practices.

Apply a business-case framework to assess a 30-minute delivery promise using a normal distribution; compute revenue, costs, and orders lost with normdist and 2.37%.

Transform raw data into outcomes through four levels: descriptive, diagnostic, predictive, and prescriptive. Move from describing and diagnosing to predicting and prescribing actions that turn insights into tangible business decisions.

Discover how to apply analytics for business by using probabilities, anomaly detection with the law of large numbers, and A/B tests for experimentation and product development.

Demonstrate how the law of large numbers drives the sample mean toward the theoretical value as sample size grows, illustrated by coin tosses and anomaly detection in business data.

Explore how the law of large numbers informs interview questions about coin toss outcomes for business leaders. See how 600, 700, or 800 heads spark discussion on bias and probability.

Explore how probability shapes decisions by distinguishing independent from dependent events and examining real-world examples like NASA satellite risks, injury odds, and bank risk profiles.

Learn how to interpret statistical significance using p-values, distinguish false positives and false negatives, and understand why a non-significant result may still be inconclusive in experiments like color-button tests.

Pfizer and publication bias are explored in a case study that shows how false positives and negatives skew results, highlighting the need for data disclosure, peer review, and rigorous methodology.

Learn why A/B tests are the gold standard for experimentation and how to design randomized, controlled trials with a single treatment, a defined KPI, and sample size and power planning.

Booking.com demonstrates a fearless experimentation culture, running about 1,000 on-site experiments and 25,000 annually, embracing overlapping tests to learn from interactions and ensuring no experiment is rejected.

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Master data driven decision making by applying the scientific method, exploring data biases through case studies, and pausing to form your own solution before reasoning.

Define problem, gather the right data, analyze, challenge assumptions, decide, and iterate in a data-driven decision-making process to optimize outcomes, while recognizing correlation is not causation and avoiding false positives.

Define the problem through a scientific, hypothesis-driven, data-driven approach to decision making; evaluate Croatia expansion using criteria like costs, infrastructure, currency, labor laws, delivery time, and customer value.

Acquire complete, representative data by blending quantitative and qualitative insights, ensuring comparability to avoid censorship bias. Learn from Abraham Wald's wartime example to prevent misleading decisions.

Learn how data acquisition and granular segmentation reveal Simpson's paradox, where the overall success rate appears higher than rates within each kidney stone subgroup, as illustrated by surgeries.

Explore data acquisition through four major BI tools, comparing Power BI, Tableau, Google Data Studio, and MicroStrategy, and learn how each tool handles unstructured data, dashboards, and visualizations.

Analyze from multiple angles to reduce false positives and negatives and avoid data manipulation, as the power posing story shows the importance of replication and avoiding p-hacking.

Explore biases such as confirmation bias and omitted variable bias, and apply the 4 eye policy to invite critique and find blind spots with a sparring partner.

Explore how omitted variable bias misattributes outcomes to sustainability practices, and see how people and culture drive decisions that influence share price performance and cost of capital.

Explore why correlation is not causation and how to spot spurious links, using the MMR vaccine and autism example, then assess causality with analytics to avoid misleading a KPI.

Explore the mutual causality bias, the chicken or egg problem where interconnected KPIs like price, quantity, and discounts influence one another in a never-ending cycle.

Distinguish self-selection from selection bias using a voluntary training example. Explain how age and life expectancy create two non-comparable groups, masking a true causal link between smoking and Parkinson's.

Explore how confirmation bias shapes data interpretation and news analysis, using a bus shooting example to show how beliefs skew evidence and data literacy for leaders.

Make informed risk-based decisions by comparing expected value and net gain across options, recognize that outcomes don’t reflect quality, and focus on positive long-term value.

Iterate on decisions to optimize outcomes, since tests have limits and can yield false positives or negatives; understanding base rates helps interpret positive results and avoid misread data.

Study data-driven public speaking, practice relentlessly, seek feedback, and hone your craft to improve. Complete a data-based final presentation and share slides for peer feedback.

Master key principles for communicating with data. Use simple language, know your audience, and keep messages concise while anticipating questions, providing context, and presenting conclusions early to drive engagement.

Learn to craft effective visualizations by avoiding print screens, leveraging conventions, and ensuring charts answer your audience's questions to make data engaging and clear.

Learn to handle presentation challenges by taking audience perspectives, preparing for criticism, and building allies, with practical steps to clarify data, respond politely, and align stakeholders.

Craft a data-driven product roadmap for the online course business, weighing self-produced courses against Udemy and Zero to Mastery partnerships to maximize revenue and minimize development and Q&A effort.

Conclude the course with confidence and boost your professional visibility by leaving a review and sharing your certificate on LinkedIn to open doors.