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| Section | Weight | Objectives |
|---|---|---|
| Predictive Analytics & Regression | 20% | - Interpreting coefficients, R-squared, significance - Simple & multiple linear regression - Forecasting & trend analysis |
| Foundations of Data-Driven Decision Making | 20% | - Ethics, privacy, and data governance - Types of analytics: descriptive, predictive, prescriptive - Role of data in business decisions |
| Statistical Concepts & Descriptive Analytics | 25% | - Data types, measurement scales, sampling methods - Data visualization: charts, graphs, dashboards - Measures of central tendency, dispersion, distribution |
| Probability & Statistical Inference | 20% | - Probability rules, distributions, expected value - Hypothesis testing, p-values, confidence intervals - Correlation vs. causation |
| Decision Models & Prescriptive Analytics | 15% | - Decision trees, payoff matrices, expected value - Quality & process improvement tools - Optimization, sensitivity analysis |
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NEW QUESTION # 74
A student with a degree is presumed to already have a bachelor's degree. Which type of data does this represent?
Answer: B
Explanation:
This question refers to categorizing information rather than measuring it numerically. The phrase "a student with a degree" identifies a classification or label, not a value with mathematical meaning. Nominal data are used to place observations into distinct categories without any inherent numerical order or ranking. In this case, the student is being grouped according to degree status, which is a named category. Interval and ratio data are numerical measurement scales, so they do not apply here. Ordinal data involve ranked categories, such as low, medium, and high, or freshman through senior, where order matters. Here, the information does not describe rank or position; it simply identifies a class of person based on a characteristic. Even though the phrase mentions a bachelor's degree, the key issue is that the information is categorical rather than numeric.
Therefore, this is best understood as nominal data. In data analysis, recognizing nominal variables is important because they are usually summarized with counts, percentages, or category-based comparisons rather than means or standard deviations.
NEW QUESTION # 75
How does a balanced scorecard (BSC) differ from a key performance indicator (KPI)?
Answer: A
Explanation:
Akey performance indicator (KPI)measures performance in asingle critical area, such as revenue growth or customer satisfaction. In contrast, abalanced scorecard (BSC)provides amulti-dimensional view of organizational performance, typically across financial, customer, internal process, and learning perspectives.
Data-driven decision making emphasizes that relying on a single metric can lead to incomplete or biased conclusions. The BSC addresses this by integrating multiple KPIs into a cohesive framework aligned with strategic objectives.
Therefore, optionAcorrectly explains the distinction between a KPI and a BSC.
NEW QUESTION # 76
Which two results occur when the null hypothesis is accepted using an F-test?
Choose 2 answers.
Answer: B,D
Explanation:
When the null hypothesis is accepted in anF-test, it indicates that there is no statistically significant difference between group variances or means, depending on the test design. Acceptance occurs when thetest statistic is less than the critical value, meaning the observed variation is within expected limits.
Accepting the null hypothesis implies thatno meaningful differenceexists between the samples. If the test statistic exceeded the critical value, the null hypothesis would be rejected.
Thus, the correct results areA and D.
NEW QUESTION # 77
A patient satisfaction survey was conducted at Family Practice A. The average rating of online telemedicine visits was 4.5 out of 5, while in-person visits received a 3.0 out of 5.
Which samples should be used to compare the ratings?
Answer: D
Explanation:
To make a valid comparison in data-driven decision making, samples must becomparable and drawn from the same population, differing only in the factor being evaluated. In this case, the goal is to compare patient satisfaction between online telemedicine visits and in-person visits atFamily Practice A.
Usingonline Family Practice A telemedicine visits and in-person Family Practice A visitsensures that both samples come from the same organization, patient base, and survey methodology. This controls for external factors such as practice standards, demographics, and survey design, allowing differences in ratings to be attributed to the visit type rather than unrelated variables.
Comparing total visits to only one visit type introduces imbalance. Including other family practices introduces external variation and invalidates the comparison. Data-driven decision making stresses consistency and relevance in sample selection to ensure accurate conclusions.
Therefore, the correct answer isD, as it uses comparable samples that isolate the variable of interest.
NEW QUESTION # 78
What is the purpose of the quality management principle of dedication to fact-based decision-making?
Answer: C
Explanation:
The principle offact-based decision-makingemphasizes using reliable data and objective analysis rather than intuition or opinion. In data-driven decision making, this principle exists primarily toreduce bias and increase trust in organizational plans and decisions.
When decisions are grounded in verified data, assumptions are challenged, personal biases are minimized, and outcomes are more predictable. This builds confidence among stakeholders and supports transparency and accountability.
Customer loyalty, waste elimination, and quality effectiveness may be indirect benefits, but the core purpose is ensuring that decisions are objective, defensible, and evidence-based. Therefore, the correct answer isD.
NEW QUESTION # 79
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