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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Probability & Statistical Inference | 20% | - Correlation vs. causation - Hypothesis testing, p-values, confidence intervals - Probability rules, distributions, expected value |
| Topic 2: Foundations of Data-Driven Decision Making | 20% | - Role of data in business decisions - Ethics, privacy, and data governance - Types of analytics: descriptive, predictive, prescriptive |
| Topic 3: Predictive Analytics & Regression | 20% | - Forecasting & trend analysis - Simple & multiple linear regression - Interpreting coefficients, R-squared, significance |
| Topic 4: Statistical Concepts & Descriptive Analytics | 25% | - Data visualization: charts, graphs, dashboards - Measures of central tendency, dispersion, distribution - Data types, measurement scales, sampling methods |
| Topic 5: Decision Models & Prescriptive Analytics | 15% | - Quality & process improvement tools - Optimization, sensitivity analysis - Decision trees, payoff matrices, expected value |
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NEW QUESTION # 99
What results from starting an analysis with flawed data?
Choose 2 answers.
Answer: B,C
Explanation:
Starting an analysis with flawed data significantly undermines the effectiveness of data-driven decision making. One major consequence is thatmore time is spent managing data than analyzing data. Analysts must devote substantial effort to cleaning, validating, and correcting errors before meaningful analysis can occur, delaying insights and increasing costs.
Another critical result is thatmissing data tend to skew the results of the analysis. Incomplete data can distort averages, trends, and statistical relationships, leading to biased conclusions and unreliable decisions.
This is especially problematic in predictive and inferential analytics, where assumptions about data completeness are essential.
Using spreadsheets or placing data in charts does not inherently result from flawed data, nor does it resolve data quality issues. While visualization can help identify errors, it is not a direct outcome of starting with flawed data.
Data-driven decision making emphasizes that poor-quality input leads to poor-quality output. Ensuring data accuracy and completeness before analysis is essential for producing valid insights. Therefore, the correct answers areB and D.
NEW QUESTION # 100
How is a cause-and-effect diagram used?
Answer: C
Explanation:
A cause-and-effect diagram, also known as an Ishikawa diagram or fishbone diagram, is used to brainstorm and organize possible root causes of a problem. It helps teams think systematically about why a problem may be occurring by grouping causes into logical categories such as methods, materials, people, equipment, and environment. In the scenario given, an intermittency problem suggests an issue that happens irregularly and may be difficult to isolate, which makes a cause-and-effect diagram especially useful. Its purpose is not to assign blame but to support structured problem-solving and root cause analysis. It is also not a financial risk tool or an automated software diagram generator. In quality management and data-driven improvement, this diagram encourages teams to explore multiple contributing factors before deciding on corrective action.
Therefore, the correct answer is that it is used to brainstorm possible root causes for an intermittency problem.
NEW QUESTION # 101
Why would a human resources department use both mean and median when doing a salary evaluation of a department?
Answer: C
Explanation:
Using both mean and median helps identifyoutliers, such as very high executive salaries that skew the average. A large difference between the two indicates uneven distribution.
Thus, the correct answer isC.
NEW QUESTION # 102
A company's marketing team tells an analyst that fewer customers are opening emails in the recent email campaign. The analyst interviews a few marketing coordinators and discovers changes were made to the email subject line between the earlier successful email campaign and the recent one. The analyst then uses a statistical technique to compare the email open rates for each campaign. Which step does the comparison of the email open rate represent in the plan-do-check-act cycle?
Answer: C
Explanation:
The plan-do-check-act cycle is a continuous improvement framework used in quality management and process improvement. In this scenario, the comparison of email open rates represents the check stage. After identifying a possible cause of the problem, the analyst uses a statistical technique to evaluate results and determine whether the changes in subject lines are associated with lower open rates. The check step is where performance is measured, reviewed, and compared against expectations or prior outcomes. The plan stage would involve deciding what change or test to make. The do stage would involve implementing the campaign or the revised subject line. The act stage would involve standardizing the successful change or making further adjustments based on the findings. Because the analyst is examining and comparing the results of the campaigns, this clearly aligns with the check phase. Therefore, the correct answer is check.
NEW QUESTION # 103
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: C
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 # 104
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