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| Section | Objectives |
|---|---|
| Hypothesis Testing | - Null and alternative hypotheses - t-tests, chi-square tests, and significance testing |
| Regression and Correlation Analysis | - Interpreting correlation and causation - Linear regression modeling |
| Decision Making Models | - Risk and uncertainty in decision-making - Decision trees and expected value analysis |
| Data Fundamentals and Business Analytics | - Data types and data collection methods - Descriptive statistics (mean, median, variance, standard deviation) |
| Probability and Statistical Inference | - Sampling methods and sampling error - Probability concepts and distributions |
>> Data-Driven-Decision-Making Certification Test Answers <<
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NEW QUESTION # 91
A researcher wants to estimate the average wholesale price of a gallon of gas in the United States. Several gas station owners along the East Coast are asked what price they pay wholesale for a gallon of gas. The researcher then averages these values for the sample mean price of a gallon of gas. Which problem would be discovered if this researcher's work were evaluated?
Answer: A
Explanation:
The key problem in this study is that the sample is not representative of the entire population. The researcher is attempting to estimate the average wholesale gas price for the whole United States, but only collects data from gas station owners along the East Coast. Because regional gas prices can differ due to transportation costs, taxes, regulations, supply conditions, and market structure, using only one geographic area creates a sampling problem. A representative sample should reflect the diversity of the full population being studied. In this case, the population includes gas stations from all parts of the country, not just one region. There is no information suggesting faulty calibration, since no measuring instrument is involved. Response bias is also not the primary issue because the scenario does not indicate that respondents are misreporting prices.
Conscious bias is less appropriate because the most obvious flaw is the limited sampling frame. This is a classic example of sampling bias caused by undercoverage. Therefore, the correct answer is that the sample data are not representative of the population.
NEW QUESTION # 92
What are two benefits of good data quality management in improving business decision-making?
Choose 2 answers.
Answer: A,B
Explanation:
Good data quality management plays a critical role in improving business decision-making by ensuring that data is accurate, complete, and reliable. One key benefit is that itensures there are no missing data points, which helps maintain data completeness. Missing data can distort results, reduce analytical power, and lead to incorrect conclusions, especially in descriptive and inferential statistics.
Another important benefit is that data quality managementmitigates undetected errors from the data-entry process. Errors such as duplicate entries, incorrect values, or inconsistent formats can significantly bias analysis if left unnoticed. Through validation checks, cleaning procedures, and governance standards, organizations reduce the risk of flawed insights.
While good data quality supports better analysis, it does not guarantee statistical significance, as significance depends on sample size, variability, and study design. Similarly, it does not necessarily make the statistical process faster; in fact, data cleaning can be time-consuming. However, it improves theaccuracy and trustworthinessof outcomes.
In data-driven decision making, high-quality data is essential because decisions are only as good as the data used to support them. Therefore, the correct answers areA and D.
NEW QUESTION # 93
An entrepreneur wants to start a boutique cupcake business based on family recipes shared for three generations. The entrepreneur knows the required costs associated with rent, supplies, utilities, and hourly wages and wants to determine how many cupcakes they need to sell to generate a profit.
Which technique should be used to analyze this data?
Answer: D
Explanation:
Break-even analysisis the appropriate technique for determining the number of units that must be sold to cover all fixed and variable costs. In data-driven decision making, break-even analysis is widely used for pricing, production, and startup feasibility decisions.
In this scenario, the entrepreneur already knows fixed costs such as rent and utilities, as well as variable costs like supplies and hourly wages. Break-even analysis calculates the point at which total revenue equals total cost, meaning profit is zero. Any sales beyond this point result in profit.
Crossover analysis is not a standard financial technique, t-tests are used to compare means, and regression analysis is used to predict outcomes based on relationships between variables rather than identify cost- revenue thresholds.
By applying break-even analysis, the entrepreneur can determine the minimum number of cupcakes required to sustain the business and make informed operational decisions. Therefore, the correct answer isB.
NEW QUESTION # 94
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 # 95
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 # 96
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