Arizona State University (ASU) WPC 300 Problem Solving and Actionable Analytics Class number Practice Exam

These questions are part of the practice quiz. Start practicing

• What does external validity mean in analytics experiments?
• Poisson distribution is applied for:
• In multi-dimensional analysis, which operation involves analyzing a smaller cube by selecting a subset across dimensions?
• What is a business case in analytics?
• Which statement best defines a confidence interval?
• Which data type is used as a label rather than a numeric measure?
• Which statement about confidence intervals is true?
• Which is a prudent constraint in the analysis process?
• Time series forecasting is commonly used for which scenario?
• Which term describes the process of explaining how data moves from its origin to its final form, including transformations and storage?
• Which of the following logic trees starts with sub-elements on the left and the problem statements to the far right?
• Which is not a best-practice for a work plan?
• What is a dashboard, and what are best practices for design?
• If you observe a drop in conversion rate after a website change, what steps would you take to diagnose the issue?
• How have managerial skills evolved in the 21st century?
• Which is an example of a continuous data variable?
• According to Occam's razor, which hypothesis is preferred?
• What is the role of data visualization in analytics?
• In the Pacific Salmon case, tree pruning was necessary because:
• It is often difficult to see the structure of the problem; team brainstorming is hugely valuable, especially when trying different lenses or cleaving frames. Which practice is this describing?
• What factors influence the choice of visualization type for a dataset?
• Which statement correctly defines a KPI?
• For a unicorn that has a 1.1% chance of hitting a $1 billion payoff, which is the expected value in millions of dollars?
• Edward Deming is associated with which problem solving framework?
• Which statement best defines data cleaning and identifies two common techniques?
• What ethical considerations arise when handling sensitive data in analytics projects?
• Time series forecasting is used for what purpose?
• Data lineage helps ensure data quality and traceability. Which statement best explains its practical purpose?
• Which practice helps reduce bias when estimating treatment effects in observational studies?
• Which heuristic would you use to understand whether your startup will run out of cash?
• In a university analytics context, which statement best distinguishes a metric from a KPI?
• What are the parameters of the standard normal distribution described in the material?
• The best-practice approach suggests that assigning specific tasks (who is doing what) is key to the successful work plan. Which option best aligns with this?
• Which logic tree would include an 'if-then' structure where you could explore potential outcomes of each decision?
• Which statement best describes a KPI?
• What makes analytics insights actionable, and how can you improve actionability in a report?
• What are common data cleaning steps before analysis?
• Which option best describes the relationship between hypotheses and analyses?
• Which problem statement requires 'analytical' skill to solve?
• Regression analysis is used in business analytics to model relationships between a dependent variable and one or more independent variables. Which of the following is a common use?
• What challenges arise with data integration from multiple systems and how can you address them?
• What are best-practice guidelines for data visualization to convey insights effectively?
• Which of the following is not a characteristic of good problem statements?
• Whys as a problem-solving method were developed at which company?
• Which scenario illustrates availability bias?
• Which statement best differentiates correlation from causation?
• What best describes root cause analysis?
• What is bias in data and how can it be mitigated?
• Which sequence correctly represents ETL?
• Five Whys problem-solving method originated at which company?
• In the context of work planning, which is a reasonable expectation?
• Which statement reflects a core aspect of data ethics?
• In experiments, causality is established as a relationship where changes in one variable cause changes in another, typically via what design?
• How would you classify descriptive, diagnostic, predictive, and prescriptive analytics with simple examples?
• In the hypothesis testing you are conducting, the confidence level needed is 99%. For you to reject the null hypothesis, the p-value needs to be:
• Which item is NOT typically evaluated in a data quality assessment?
• As a farmer interested in data-driven decision-making, you want to determine the effect of 3 fertilizers on your crop yield. Which hypothesis testing would you use to determine if there is any difference in the yield between the three fertilizers?
• Which practice is most closely associated with ensuring traceability of data from source to analysis?
• Power analysis is used to determine what in experimental design?
• What step of the bulletproof problem-solving process helps avoid making common decision-making biases such as sunk cost fallacy?
• In hypothesis testing, the null hypothesis typically states what?
• What is the primary purpose of data visualization best practices?
• A hypothesis test is a procedure to determine if observed data deviates significantly from a null hypothesis. Which concept does this describe?
• In analytics, when would you use a t-test versus a chi-square test?
• Which statement identifies an objective in an analytics project?
• Which cycle is correctly ordered as Plan, Do, Check, Act?
• How would you differentiate primary data sources from secondary data sources in analytics projects?
• What is data storytelling?
• In a multi-dimensional analysis, keeping one of the dimensions constant and analyzing two dimensions of a cube is called.
• Which statement describes a measurement plan characteristic?
• Which is NOT a typical step in exploratory data analysis (EDA)?
• Data governance is best described as which of the following?
• In hypothesis testing, type II error occurs when:
• To explain a complex model to a non-technical stakeholder, which approach is recommended?
• Which is a true statement about one-day answers?
• The value of actionability in analytics refers to insights that translate into concrete, implementable steps that drive business decisions. Which best describes it?
• Which statement correctly contrasts structured and unstructured data?
• What is a KPI?
• Which statement best describes Occam's razor?
• Differentiate between metrics and KPIs with examples relevant to a university analytics context.
• Which data type uses numbers to label categories with no inherent order?
• What is a hypothesis in statistical testing?
• What is the best way to improve the problem statement 'Reduce our operating costs'?
• Which statement correctly contrasts descriptive and diagnostic analytics?
• What is MoSCoW prioritization?
• Which heuristic is used in situations involving compounding growth?
• Which technique is commonly used to address missing values during data cleaning?
• In experiments, what is a control group?
• Which measure is not used in describing a continuous data variable?
• Which of the following is an example of a discrete random variable?
• One-day answers clarify where you are and what work is left to do—and provide a straw man for pressure-testing your work.
• How can the problem statement be improved?
• Which statistic describes the spread of a continuous variable?
• Which statement best describes the relationship between correlation and causation?
• Which of the following is a limitation of the reasoning by analogy heuristic?
• Which data type uses numbers as identifiers with no real meaning?
• What does 'disaggregate' refer to in bulletproof problem solving?
• Which statement best describes the role of time perspective in projects?
• In A/B testing, what is the primary purpose?
• What is a common storytelling framework for analytics insights, and how should it be used?
• The tools and elements in this frame come from game theory and include concepts such as multi‐play games and reputation. Which frame is this?
• In a multi dimensional analytical operation, analyzing a smaller version of a cube is called:
• Which regression method is correctly matched with its typical use?
• Which of the following is not one of the seven steps in bulletproof problem solving?
• Frequency is typically used to describe which type of variable?
• How do you map business questions to analytics deliverables in a project plan?
• In general, problem‑solving steps benefit substantially from which of the following?
• How are control charts used to monitor performance, and what actions indicate a need for investigation?
• Which statement best describes the primary objective of problem framing in a data analytics project?
• A problem disaggregation element is mutually exclusive. Which option best describes this property?
• How do you validate a predictive model to ensure reliability before deployment?
• Why is reproducibility critical in analytics, and what practices support it?
• Which statement is consistent with the best practice?
• In analytics project planning, what is an example of a deliverable?
• In cost-benefit analysis, how are cash flows used to compute net present value?
• What is the best approach to determine the right metrics for a project?
• Data can be used to disaggregate problems by revealing multiple dimensions of the problem. True or False?
• What does winsorizing mean in data preparation?
• What is the purpose of a data dictionary?
• In predictive modeling, what describes overfitting?
• What is backtesting in predictive model validation?
• What are the components of a cost-benefit analysis in data analytics?
• What are the common pitfalls of multiple hypothesis testing and how can you mitigate them?
• During a problem disaggregation process, you find each element represented in the tree is completely unique. This means that each element is:
• Why is data governance important in analytics projects, and what practices support it?
• During the problem disaggregation process, the logic trees should have branches that are:
• What is the purpose of a data dictionary in analytics projects?
• A continuous random variable x is normally distributed with a mean of 0 and a standard deviation of 1. The probability of an observation that lies within the range of -1.0 < x < 1.0 is:
• What are key considerations when designing dashboards for decision-makers?
• Which of the following is a characteristic of good problem statements?
• Which of the following is NOT typically part of the problem framing process?
• What is the role of a data dictionary in analytics?
• Which principle best describes a valuable metric?
• What best describes an actionable insight in the S-C-R framework?
• What makes ratio data distinct from other data types?
• In an experiment, what is the difference between a treatment group and a control group?
• What is the main purpose of problem framing in analytics projects?
• How is ROI calculated in business analytics?
• Which metric is most appropriate to assess a classifier's discrimination performance?
• What does a data dictionary describe?
• What does getting an order of magnitude understanding imply?
• In ethics, which principle says data should be used only for the stated purpose?
• What does a p-value indicate in the context of A/B testing?
• Which of the following is a fundamental step in the bulletproof problem solving process?
• Which items are considered key components of a problem statement in WPC 300?
• Which one of the following is not a characteristic of good problem statements:
• Which statement about common time-series forecasting approaches is true?
• Which hypothesis testing method would you use to determine the impact of a drug when you measure patients before and after treatment?
• Why is seasonality and trend important in time-series analytics, and how can you account for it?
• What is the difference between supervised and unsupervised learning?
• Which statement describes a comprehensive approach to best-practice work plans?
• In a data dictionary, what does lineage describe?
• The root cause analysis uses one of the following techniques:
• Which of the following is NOT a recommended mitigation for bias in analytics?
• Which statement best distinguishes leading indicators from lagging indicators?
• Which statement is NOT true about good practice principles of data ethics?
• Which of the following describes a typical ETL data pipeline and its components?
• Cross-validation is used to do what?
• What is confounding in an experiment, and how can randomization help mitigate it?
• What is statistical power and why is it important for experiment design?
• What does ROI stand for in analytics?
• Which of the following is an example of a KPI?
• Which of the following is an example of nominal data?
• How is the 5 Whys technique used in problem analysis?
• In MoSCoW prioritization, what does 'Must have' mean for project features?
• Which chart type is used to show prediction over time and is not typically used to describe the data?
• At 20% annual growth, starting from 1,000,000 dollars, when will the startup reach 4,000,000 dollars in revenue?
• Which of the following chart types is generally not used for data exploration?
• Which of the following best describes the nature of hypotheses in problem solving?
• Which of the following describes common strategies to address missing data?
• What is logistic regression and when is it appropriate?
• Holding a single dimension fixed to examine the other two dimensions is known as which operation?
• What should be included in a measurement plan for an analytics project?
• Which statement best describes analyses in a best-practice work plan?
• ETL stands for what?
• Which sequence correctly represents the DMAIC framework?
• Which step in bulletproof problem solving is primarily about communicating the plan and findings?
• Referential integrity in data quality means what?
• In time-series forecasting, which method is commonly used for decomposing seasonality and trend?
• Which approach is suitable for forecasts when there is a clear trend and seasonality and you want to decompose the series into components?
• Which practice helps mitigate bias in data and modeling?
• Which expression correctly computes the expected value when the unicorn probability is 1.1% and the payoff is $1 billion?
• Poisson distribution is applied for which type of random variable?
• Which element helps define whether a project meets stakeholder expectations and is used to judge success?
• True/False: A straw man is used for pressure-testing your work.
• Which statement best describes the ICE prioritization framework?
• Which statement correctly describes Type I and Type II errors and their relation to significance level and power?
• Which of the following are not examples of measures in a multi-dimensional analysis:
• In prescriptive analytics, what is the typical outcome?
• Data lineage describes the data's origin and its movement through transformations to its final form. Which of the following best reflects its purpose?
• What is data governance?
• What is the purpose of Ishikawa (fishbone) diagrams in analytics and quality work?
• Which statement best describes the role of SQL in data analytics, and what is a minimal example query to select students with a GPA above 3.5?
• Ethics in analytics include which principles?
• What is the primary purpose of sensitivity analysis?
• What is an ETL pipeline, and why is it important for actionable analytics?
• In the example with the newspaper, the primary issue with the problem framing was:
• Which heuristic will the company use to perform analysis in a scenario involving compounding growth?
• David asked repeatedly a why-type question to analyze a problem. What does he produce eventually?
• Which of the following statements about KPI is true?
• How can bias enter analytics results and what are mitigation strategies?
• Which statement correctly describes Monte Carlo simulation?
• What is normalization in data preprocessing?
• What is the purpose of conducting a data quality assessment?
• If a disease grows at 12% per week starting from 100,000 infected, how many weeks will it take to reach 800,000?
• What is a confidence interval and what does it tell you about an estimate?
• What is the difference between a predictive and a prescriptive model?
• True or False: Data cannot be used to disaggregate problems.
• How is a p-value best interpreted in hypothesis testing?
• When designing experiments with small sample sizes, what is a key consideration?
• Which element is explicitly addressed to reflect decision maker values and boundaries in a well-formed problem statement?
• Which analytics type is used to summarize data and provide a quick snapshot?
• What is Monte Carlo simulation used for?
• What is the difference between business analytics and data analytics?
• How do you estimate sample size for a proportion in an A/B test?
• A critical analysis based on heuristics will lead to:
• In the case of Pacific Salmon, which logic tree helped us see the big levers that affect the abundance of salmon in the Pacific Ocean?
• What does SMART stand for in objective setting for analytics projects?
• Which is a typical category used in Ishikawa diagrams?
• What is a recommended approach to handling outliers in a dataset?
• When should you stop an experiment early, and what criteria should guide that decision?
• Which of the following describes a basic ROI analysis for analytics?
• In descriptive analytics, what is the primary objective?
• How can regression analysis be used in business analytics?
• What are the essential features of a well-designed A/B test?
• In A/B testing, why is random assignment important?
• When should you typically use a one-tailed test versus a two-tailed test?
• What is the effect of making the problem statement specific, measurable, and time-bound?
• Which option best represents data quality checks commonly performed at the start of an analytics project?
• In root cause analysis, what is the purpose of a fishbone (cause-and-effect) diagram?
• If you need to forecast a numerical outcome based on other variables, which technique would you use?
• Data lineage is best described as which of the following?
• During the pruning process, we remove elements of the disaggregation that have:
• How can you distinguish root causes from symptoms in analytics problems?
• Which data type is exemplified by a person's body weight?
• Which statement describes the break-even point?
• Which practice best supports accountability in analytics projects?
• Explain why correlation does not imply causation and how you can assess causality in analytics projects.