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| Section | Objectives |
|---|---|
| Decision Making Models | - Risk and uncertainty in decision-making - Decision trees and expected value analysis |
| Probability and Statistical Inference | - Sampling methods and sampling error - Probability concepts and distributions |
| Hypothesis Testing | - Null and alternative hypotheses - t-tests, chi-square tests, and significance testing |
| Regression and Correlation Analysis | - Linear regression modeling - Interpreting correlation and causation |
| Data Fundamentals and Business Analytics | - Data types and data collection methods - Descriptive statistics (mean, median, variance, standard deviation) |
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NEW QUESTION # 71
What results from starting an analysis with flawed data?
Choose 2 answers.
Answer: A,B
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 # 72
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 # 73
A normally distributed data index of vehicle safety ratings has a mean of 100 and a standard deviation of 15.
What is the probability that a randomly selected vehicle safety score from the data set will be between 85 and
115?
Answer: B
Explanation:
The interval from 85 to 115 is exactly one standard deviation below and above the mean, since the mean is
100 and the standard deviation is 15. In a normal distribution, the empirical rule states that approximately 68 percent of observations fall within one standard deviation of the mean, about 95 percent fall within two standard deviations, and about 99.7 percent fall within three standard deviations. Because the range 85 to 115 corresponds to mean ยฑ 1 standard deviation, the probability of selecting a score in that range is about 68 percent. Among the available options, 68.8 percent is the correct choice and best represents this probability.
The other values correspond to wider intervals: 95.4 percent is associated with two standard deviations and
99.7 percent with three. A value of 100 percent would imply every possible score lies in that range, which is not true for a normal distribution. Therefore, the correct answer is 68.8 percent because the question describes the one-standard-deviation interval around the mean.
NEW QUESTION # 74
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 # 75
A major hospital system wants to improve its level of patient satisfaction. Management has recently asked patients to complete a survey as part of the discharge process. From this survey, a net promoter score is derived and tracked over time. What does a net promoter score reveal?
Answer: C
Explanation:
A net promoter score reveals the strength of an organization's customer relations by measuring how likely customers are to recommend the organization to others. In a hospital setting, patients are the relevant customer group, and their willingness to recommend the hospital reflects satisfaction, trust, and overall experience. Because the score is tracked over time, management can use it as an indicator of whether customer relationships are improving or declining. A higher net promoter score generally suggests stronger loyalty and more positive perceptions, while a lower score may indicate service or quality concerns. The score is not about how management feels about employees, nor is it used to track employee advancement. It may be influenced indirectly by marketing, but it does not primarily measure advertising campaign effectiveness. Its main purpose is to provide a clear signal about customer loyalty and relationship strength. Therefore, the correct answer is the strength of an organization's customer relations.
NEW QUESTION # 76
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