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| Section | Objectives |
|---|---|
| Topic 1: Probability and Statistical Inference | - Sampling methods and sampling error - Probability concepts and distributions |
| Topic 2: Regression and Correlation Analysis | - Linear regression modeling - Interpreting correlation and causation |
| Topic 3: Decision Making Models | - Decision trees and expected value analysis - Risk and uncertainty in decision-making |
| Topic 4: Hypothesis Testing | - t-tests, chi-square tests, and significance testing - Null and alternative hypotheses |
| Topic 5: Data Fundamentals and Business Analytics | - Descriptive statistics (mean, median, variance, standard deviation) - Data types and data collection methods |
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NEW QUESTION # 96
Which two statements describe Ishikawa's seven basic tools of quality?
Choose 2 answers.
Answer: B,C
Explanation:
Ishikawa'sseven basic tools of qualitywere designed to be simple, visual, and accessible. In data-driven decision making, these tools help employees identify, analyze, and solve quality problems without requiring advanced statistical expertise.
The tools-such as flowcharts, histograms, Pareto charts, and cause-and-effect diagrams-represent processes graphically, making patterns and issues easier to understand. Additionally, they are intentionally designed so thatan average worker can easily understand and use them, supporting organization-wide quality improvement.
They do not rely on photographic representations, nor are they intended for advanced or expert-level training.
Instead, they empower frontline employees to participate in continuous improvement efforts.
Therefore, the correct answers areA and C.
NEW QUESTION # 97
What does big data include?
Answer: B
Explanation:
Big data includes both structured and unstructured data. Structured data are organized in predefined formats such as rows and columns in databases, spreadsheets, or transaction systems. Unstructured data include forms such as emails, videos, social media content, images, audio files, sensor outputs, and free-text documents that do not fit neatly into traditional tabular formats. One of the defining features of big data is not just its size, but also its variety. This variety means organizations must work with multiple data types and sources to generate useful insights. The other options do not define what big data includes. Spreadsheets may handle small portions of data, but they do not define the concept itself. Powerful extraction tools may be used in big data environments, but they are tools rather than components of the data. Inferential statistics are analytical methods, not the data itself. Therefore, the best answer is that big data includes both structured and unstructured data.
NEW QUESTION # 98
A financial analyst theorizes that commute times increase as the percentage of land availability for homes in a city decreases. To test this theory, the analyst uses a regression analysis. Which analysis result is supportive of this analyst's theory?
Answer: A
Explanation:
A regression result is most supportive of a theory when it shows a strong relationship between the independent and dependent variables. In this case, the analyst believes that commute times rise as land availability for homes falls. Among the answer choices, an R-squared value of 0.90 provides the strongest support because it indicates that about 90 percent of the variation in commute times is explained by the regression model. This suggests a very strong model fit. By contrast, an R-squared value of 0.10 would indicate a weak explanatory relationship. The p-values of 0.50 and 1 do not support the theory because large p- values suggest that the regression coefficient is not statistically significant. In regression analysis, a low p- value typically supports the idea that the predictor variable has a meaningful relationship with the outcome variable. Since no low p-value is offered, the best supportive result among the choices is the high R-squared value. Therefore, the correct answer is 0.90 because it indicates the model strongly explains the observed pattern.
NEW QUESTION # 99
Two vendors sell a dozen raw materials that a company needs to build its products. Which type of analysis should be used to determine if one of the vendors has a better average price at a given point in time?
Answer: A
Explanation:
To determine whether one vendor has a better average price than another, the company should use data analysis. This is the broad analytical approach that involves collecting pricing information, organizing the values, comparing averages, and possibly applying additional statistical methods to evaluate the difference.
The task is numerical and evidence-based, making data analysis the correct and most complete choice.
Heuristic analysis usually refers to rule-of-thumb decision methods rather than direct statistical comparison.
Background analysis is not the standard term for comparing measurable pricing information. Graphical analysis may help visualize price differences, but graphs alone do not fully describe the method needed to determine average pricing performance. Because the question asks which type of analysis should be used to compare average price, the answer is the one that directly refers to analyzing the numerical data itself.
Therefore, the correct answer is data analysis.
NEW QUESTION # 100
A healthcare organization implements a campaign to improve patient satisfaction during recent stays. The average patient satisfaction before the campaign is M = 4.20, SD = 3.0. Six months after the new campaign, the average patient satisfaction is M = 1.5, SD = 2.0.
Which action should the hospital management team take?
Answer: A
Explanation:
Data-driven decision making requires comparing outcomes before and after an intervention to assess effectiveness. In this scenario, the mean patient satisfaction scoredeclined from 4.20 to 1.5following implementation of the campaign, indicating a substantial decrease in satisfaction.
Despite the reduced standard deviation, the large drop in the mean suggests the campaign did not achieve its intended goal and may have negatively affected patient experience. Continuing or modifying the campaign is not justified without evidence of initial improvement or external factors explaining the decline.
Management decisions must be grounded in outcome data rather than assumptions or unrelated metrics such as patient volume. Ethical and effective use of statistics requires discontinuing interventions that demonstrably worsen outcomes.
Therefore, the correct action is todiscontinue the campaign, making optionAthe correct answer.
NEW QUESTION # 101
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