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| Section | Objectives |
|---|---|
| Topic 1: Data Fundamentals and Business Analytics | - Data types and data collection methods - Descriptive statistics (mean, median, variance, standard deviation) |
| Topic 2: Decision Making Models | - Decision trees and expected value analysis - Risk and uncertainty in decision-making |
| Topic 3: Hypothesis Testing | - t-tests, chi-square tests, and significance testing - Null and alternative hypotheses |
| Topic 4: Regression and Correlation Analysis | - Linear regression modeling - Interpreting correlation and causation |
| Topic 5: Probability and Statistical Inference | - Probability concepts and distributions - Sampling methods and sampling error |
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NEW QUESTION # 97
What is a disadvantage of using a balanced scorecard?
Answer: A
Explanation:
A key disadvantage of using abalanced scorecardis that itrequires significant time and effort to develop a meaningful and effective template. In data-driven decision making, the value of a balanced scorecard depends on careful selection of performance measures that align with organizational strategy.
Developing a balanced scorecard involves defining strategic objectives, selecting appropriate metrics, setting targets, and ensuring data availability. This process can be resource-intensive, especially in large or complex organizations. However, once implemented, the balanced scorecard offers substantial long-term benefits.
The other options are incorrect because the balanced scorecard explicitly includes both financial and nonfinancial measures and is designed to link operations with strategy. While implementation may involve some cost, expense alone is not typically cited as its primary disadvantage.
Therefore, the correct answer isA.
NEW QUESTION # 98
Which two results occur when the null hypothesis is accepted using an F-test?
Choose 2 answers.
Answer: A,C
Explanation:
When the null hypothesis is accepted in anF-test, it indicates that there is no statistically significant difference between group variances or means, depending on the test design. Acceptance occurs when thetest statistic is less than the critical value, meaning the observed variation is within expected limits.
Accepting the null hypothesis implies thatno meaningful differenceexists between the samples. If the test statistic exceeded the critical value, the null hypothesis would be rejected.
Thus, the correct results areA and D.
NEW QUESTION # 99
An analyst used multiple linear regression to show how a big box store's sales (y) are predicted by the big box store's advertising expenditure in dollars (variable x1) and the advertising expenditure in dollars of a specialty store (variable x2) in the same market. The estimated regression is y = 651.57 + 92.30x1 # 26.89x2. How are advertising expenditures and sales related in this scenario?
Answer: D
Explanation:
The regression equation shows how each advertising variable is related to the big box store's sales while holding the other variable constant. The coefficient for x1, the big box store's advertising, is positive 92.30.
This means that when the big box store increases its own advertising expenditure, predicted sales increase.
The coefficient for x2, the specialty store's advertising, is negative 26.89. This means that as the specialty store spends more on advertising, the big box store's predicted sales decrease. Therefore, the relationship described in option A is correct. Options C and D incorrectly reverse the meaning of the positive coefficient on the big box store's own advertising. Option B is directionally true in a general sense, but the clearest direct interpretation from the equation is the negative effect of the specialty store's advertising on big box store sales, which is exactly stated in option A. Multiple regression allows analysts to isolate these effects and interpret how changes in each predictor influence the dependent variable. Thus, the correct answer is that if the specialty store increases its advertising expenditures, it will decrease the big box store's sales.
NEW QUESTION # 100
Which element is associated with control charts?
Answer: B
Explanation:
Control charts are a core tool in statistical process control and are used to monitor variation in a process over time. One of their defining features is the inclusion of upper and lower control limits. These limits help determine whether process variation is consistent with common-cause variation or whether unusual, assignable causes may be affecting performance. The chart typically includes a center line representing the process average, along with upper and lower limits that establish the acceptable range of variation under stable conditions. When points fall outside these limits or show nonrandom patterns, the process may require investigation. While hypothesis testing and correlation are important statistical concepts, they are not the primary identifying elements of a control chart. A reliability index may be used in certain engineering or quality contexts, but it is not the standard feature that defines control charts. Therefore, the element most directly associated with control charts is upper and lower limits, since those boundaries are central to evaluating whether a process remains in statistical control over time.
NEW QUESTION # 101
Two project teams are assigned to upgrade an on-premise data warehouse to a cloud-based data lake in 13 months. The infrastructure team has five team members, while the enterprise analytics team has three team members. The enterprise analytics team cannot move into production until the infrastructure team has completed the migration.
What should be used to find the probability that the project will be completed on time?
Answer: D
Explanation:
This scenario requires the use of **conditional probability**, which applies when the likelihood of one event depends on the occurrence of another event. In data-driven decision making, conditional probability is used to model dependent events within processes, workflows, and project timelines.
In this case, the enterprise analytics team's ability to move into production is **dependent on** the infrastructure team completing the migration. Because one event cannot occur unless another event has already occurred, the probability of completing the project on time must account for this dependency.
The multiplication principle applies to independent events, Bayes' theorem updates probabilities based on new information, and combinations are used for counting outcomes, not dependency analysis. Conditional probability explicitly captures the relationship between dependent tasks.
Project risk analysis and scheduling often rely on conditional probability to assess completion likelihood when tasks are sequentially linked. Therefore, the correct answer is **C**, conditional probability.
NEW QUESTION # 102
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