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| Section | Objectives |
|---|---|
| Topic 1: Hypothesis Testing | - Null and alternative hypotheses - t-tests, chi-square tests, and significance testing |
| Topic 2: Probability and Statistical Inference | - Sampling methods and sampling error - Probability concepts and distributions |
| Topic 3: Data Fundamentals and Business Analytics | - Data types and data collection methods - Descriptive statistics (mean, median, variance, standard deviation) |
| Topic 4: Decision Making Models | - Decision trees and expected value analysis - Risk and uncertainty in decision-making |
| Topic 5: Regression and Correlation Analysis | - Linear regression modeling - Interpreting correlation and causation |
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NEW QUESTION # 57
Which step in the plan-do-check-act cycle is described as analyzing the results of an experiment and deciding whether those results can be improved?
Answer: B
Explanation:
TheCheckphase of the Plan-Do-Check-Act (PDCA) cycle involves evaluating outcomes and analyzing results. In data-driven decision making, this step compares actual performance against expected results to determine whether objectives were met.
During the Check phase, organizations review data, assess variation, and identify opportunities for improvement. Planning defines objectives, Doing implements changes, and Acting standardizes or adjusts processes based on evaluation.
Therefore, the correct answer isA, Check.
NEW QUESTION # 58
A bakery owner would like to know how many cakes to sell for monthly profit to equal zero. Which analysis method should the owner perform?
Answer: D
Explanation:
The bakery owner wants to determine the sales level at which profit equals zero. This is the definition of break-even analysis. Break-even analysis identifies the number of units that must be sold so that total revenue exactly equals total cost, meaning there is neither profit nor loss. It is a widely used prescriptive and managerial decision tool for pricing, budgeting, production planning, and cost control. ANOVA is used to compare means across groups, not to find a zero-profit sales level. A t-test compares means between two groups, which is also unrelated to the goal of determining the required sales quantity for no profit or loss.
"Crossover" is not the standard term for this type of profitability calculation in business analytics. Break-even analysis helps managers understand fixed costs, variable costs, contribution margin, and the minimum output required to sustain operations. Therefore, the correct method for determining how many cakes must be sold so that monthly profit equals zero is break-even analysis.
NEW QUESTION # 59
A researcher notes that people who exercise daily tend to sleep better. The researcher then asks subjects to keep a sleep diary and record the number of hours they sleep each night. Some diaries have few entries, but the subjects claim they are well rested. Which type of error is represented in this research?
Answer: D
Explanation:
This scenario illustrates response bias because the quality and completeness of the recorded responses are questionable. The researcher depends on subjects to accurately document their sleeping hours in diaries, yet some subjects submit few entries while still claiming they are well rested. This creates a mismatch between documented evidence and self-reported perception. Response bias occurs when participants provide answers that do not fully or accurately reflect reality, whether intentionally or unintentionally. In this case, the subjects may be estimating, omitting information, or reporting what they believe sounds acceptable rather than what was consistently recorded. The problem is not mainly lack of blinding, since there is no indication that concealed treatment assignment is relevant. It is also not primarily cause-and-effect confusion, because the issue described concerns the reliability of the reported data rather than drawing a causal conclusion.
Conscious bias is less fitting because the question points to flawed responses rather than deliberate manipulation by the researcher. Therefore, the best answer is response bias, as the data collected from subjects may not accurately represent their actual sleep behavior.
NEW QUESTION # 60
What is true about outliers?
Choose 2 answers.
Answer: B,D
Explanation:
Outliers are observations that differ substantially from the rest of the data, but they are not automatically errors and should not be removed without investigation. One correct statement is that miskeyed outliers can be corrected before analysis. For example, if a value of 500 is entered instead of 50, this is a data-entry error, not a meaningful observation, and it should be fixed using source verification. Another correct statement is that outliers can help determine whether something does not belong in the study. They may reveal invalid records, unusual conditions, a different population, process breakdowns, or rare but important events. The incorrect choices are too absolute. Not all outliers are statistically significant, even under a normal distribution, because significance depends on context, sample size, and method. Likewise, not all observed outliers should be eliminated. Some outliers contain valuable information and can indicate real variation that deserves attention. In quality control, fraud detection, medical screening, and operational monitoring, outliers may be among the most important data points. Therefore, the correct answers are the ones that recognize both correction of miskeyed values and the analytical value of identifying unusual observations.
NEW QUESTION # 61
A company runs a regression analysis to determine sales based on advertising expenditures, which can be shown in a linear equation as y = 2x + 25,000. The company plans to spend $20,000 on advertising.
Which sales figure should the company expect to generate based on the given equation?
Answer: D
Explanation:
In linear regression, the equation y = mx + b is used to predict the value of the dependent variable based on the independent variable. In data-driven decision making, this equation represents the estimated relationship between advertising expenditure and sales revenue.
Here,xrepresents advertising spending,mis the slope (2), andbis the intercept ($25,000). Substituting the planned advertising expenditure of $20,000 into the equation gives:
y = 2(20,000) + 25,000
y = 40,000 + 25,000
y = 65,000
This result represents the expected sales revenue based on the regression model. The intercept indicates baseline sales when advertising spend is zero, while the slope shows the increase in sales for each additional dollar spent on advertising.
Therefore, the company should expect to generate$65,000in sales, making optionCthe correct answer.
NEW QUESTION # 62
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