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| Section | Objectives |
|---|---|
| Topic 1: Data Fundamentals and Business Analytics | - Descriptive statistics (mean, median, variance, standard deviation) - Data types and data collection methods |
| Topic 2: Hypothesis Testing | - Null and alternative hypotheses - t-tests, chi-square tests, and significance testing |
| Topic 3: Probability and Statistical Inference | - Probability concepts and distributions - Sampling methods and sampling error |
| Topic 4: Regression and Correlation Analysis | - Linear regression modeling - Interpreting correlation and causation |
| Topic 5: Decision Making Models | - Risk and uncertainty in decision-making - Decision trees and expected value analysis |
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NEW QUESTION # 13
Why is choosing appropriate performance indicators important for data-driven decision-making?
Answer: B
Explanation:
Performance indicators guide behavior, priorities, and decision-making. In data-driven decision making, selecting theright indicators ensures alignment with an organization's definition of success. Metrics determine what is measured, monitored, and improved.
If indicators are poorly chosen, organizations may optimize the wrong outcomes, leading to unintended consequences. Well-aligned indicators translate strategic goals into measurable targets and ensure that analytics support meaningful results.
Rules, motivation, and compliance may be secondary effects, but the primary purpose of performance indicators is strategic alignment. Therefore, the correct answer isC.
NEW QUESTION # 14
A county government wants to start a cost-effective recycling program. How can the county apply data analytic approaches to attain this goal?
Answer: B
Explanation:
To create a cost-effective recycling program, the county should benchmark similar strategies used by other counties. Benchmarking is a practical data-driven approach that allows decision-makers to compare program designs, costs, participation rates, collection methods, and outcomes across jurisdictions facing similar conditions. By examining how other counties structure successful recycling initiatives, the county can identify efficient practices, realistic cost expectations, and implementation strategies that have already been tested in comparable environments. This approach is especially useful when developing a new program because it reduces trial-and-error and supports evidence-based planning. The other options are less directly related to designing and evaluating a recycling program. Analyzing county contracts or aligning funds with staffing levels may be useful in general budgeting, but they do not specifically address recycling strategy effectiveness. Audit performance research is also not closely tied to recycling program design. Therefore, the most appropriate data analytic approach is benchmarking similar strategies of other counties.
NEW QUESTION # 15
A hospital hires a third-party company to train its surgery team on the latest techniques and assess the team's current procedures in the operating room.
Which results-based management (RBM) stage is represented in this scenario?
Answer: A
Explanation:
In results-based management (RBM),activitiesrepresent the actions undertaken to achieve desired outputs and outcomes. In data-driven decision making, activities include training, assessments, and implementation efforts.
Hiring a third-party company to train staff and assess procedures is an action being performed, not the result of that action. Inputs would include funding or resources, outputs would be trained staff or reports, and outcomes would reflect improved surgical performance.
Therefore, the correct answer isD, activities.
NEW QUESTION # 16
A hot tub company recently calibrated all its machines during an expensive maintenance cycle performed by an outside company. However, defective pumps with small cracks are being made on the production line. The manager reviews the data about the errors and discovers that more errors occur during the night shift than during the day shift.
Which type of activity is this manager performing?
Answer: B
Explanation:
Quality controlinvolves monitoring, measuring, and analyzing production output to identify defects and variations. In data-driven decision making, quality control focuses on detecting problems after or during production rather than preventing them in advance.
In this scenario, the manager reviews defect data and identifies a pattern indicating more errors during the night shift. This analysis is a classic quality control activity, as it involves examining performance data to detect issues in the production process.
Quality assurance focuses on process design and prevention, while service and underlying activities are not standard quality management classifications. Therefore, the correct answer isD, quality control activity.
NEW QUESTION # 17
What are random errors caused by?
Answer: A
Explanation:
Random errors are caused by unpredictable fluctuations that occur naturally in measurement, observation, or recording processes. These errors are not consistently in one direction and do not systematically push results higher or lower. Instead, they introduce variability that can make repeated measurements differ slightly even when conditions seem similar. Examples include minor environmental changes, momentary variations in instrument sensitivity, normal human reaction differences, or small observational inconsistencies. Because random errors are unsystematic, they tend to average out over a large number of observations, although they still reduce precision. By contrast, an instrument that needs calibration is more closely associated with systematic error, because it may consistently overstate or understate measurements. Respondents favoring certain outcomes and biased data also reflect systematic forms of bias rather than random variation. In statistics and quality measurement, distinguishing between random error and systematic error is important because each requires a different response. Random error is mainly addressed through repetition, sample size, and statistical controls, whereas systematic error must be corrected at the source. Therefore, the correct cause of random errors is unpredictable fluctuations in readings.
NEW QUESTION # 18
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