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| Section | Objectives |
|---|---|
| Data Fundamentals and Business Analytics | - Descriptive statistics (mean, median, variance, standard deviation) - Data types and data collection methods |
| Regression and Correlation Analysis | - Linear regression modeling - Interpreting correlation and causation |
| Decision Making Models | - Decision trees and expected value analysis - Risk and uncertainty in decision-making |
| Hypothesis Testing | - t-tests, chi-square tests, and significance testing - Null and alternative hypotheses |
| Probability and Statistical Inference | - Probability concepts and distributions - Sampling methods and sampling error |
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NEW QUESTION # 33
Phone calls for a company are routed randomly to one of eight call centers. Six are based in the United States, and two are based in another country. What is the probability that an incoming call will be routed to a U.S.- based call center?
Answer: A
Explanation:
Probability is calculated as the number of favorable outcomes divided by the total number of possible outcomes, assuming each outcome is equally likely. In this case, there are eight call centers total, and six of them are located in the United States. Since calls are routed randomly, each call center has an equal chance of receiving an incoming call. Therefore, the probability that a call is routed to a U.S.-based call center is 6 out of 8. This fraction simplifies to 3 out of 4, which is equal to 0.75 or 75 percent. The answer choices 25 percent and 33 percent are too small because they do not match the proportion of U.S. call centers. The option 67 percent is closer but still incorrect, as 6 divided by 8 is not 0.67. This is a basic probability problem involving equally likely outcomes. Because six of the eight centers are in the United States, the correct probability is 75 percent.
NEW QUESTION # 34
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 # 35
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 # 36
A spa wants to determine which duration of its massage packages is the most popular. The spa has 30-minute,
50-minute, and 75-minute sessions. Which statistical measure should be used and is less affected by outliers and skewed data?
Answer: B
Explanation:
The spa wants to know which package duration is the most popular, meaning which session length occurs most frequently in the data. The statistical measure used to identify the most frequently occurring category or value is the mode. Because the massage durations are offered in discrete categories of 30, 50, and 75 minutes, the mode is the best measure for determining customer preference. It directly identifies the package selected most often. Standard deviation measures variability, not popularity. Mean and median are measures of central tendency, but they do not answer the question of which option is chosen most frequently. Although the wording mentions being less affected by outliers and skewed data, the strongest reason to choose the mode is that popularity is fundamentally a frequency question. The mode is especially useful for categorical or discrete-choice data where the goal is to identify the most common option rather than the center of a numerical distribution. Therefore, the correct answer is mode because it shows which massage duration customers prefer most often.
NEW QUESTION # 37
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 # 38
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