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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Statistical Concepts & Descriptive Analytics | 25% | - Data visualization: charts, graphs, dashboards - Data types, measurement scales, sampling methods - Measures of central tendency, dispersion, distribution |
| Topic 2: Probability & Statistical Inference | 20% | - Probability rules, distributions, expected value - Hypothesis testing, p-values, confidence intervals - Correlation vs. causation |
| Topic 3: Foundations of Data-Driven Decision Making | 20% | - Role of data in business decisions - Types of analytics: descriptive, predictive, prescriptive - Ethics, privacy, and data governance |
| Topic 4: Predictive Analytics & Regression | 20% | - Forecasting & trend analysis - Interpreting coefficients, R-squared, significance - Simple & multiple linear regression |
| Topic 5: Decision Models & Prescriptive Analytics | 15% | - Decision trees, payoff matrices, expected value - Quality & process improvement tools - Optimization, sensitivity analysis |
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NEW QUESTION # 32
A clothing company wants to predict sales figures based on the amount spent on advertising.
Which type of regression analysis should this company use?
Answer: B
Explanation:
When predicting a continuous outcome based on a single predictor, data-driven decision making recommends simple linear regression. In this case, sales figures are continuous, and advertising spend is a single explanatory variable.
Linear regression models the relationship between one independent variable and one dependent variable by estimating a straight-line relationship. Time series regression is used when data are indexed over time, logistic regression is used for binary outcomes, and multiple linear regression requires multiple predictors.
Because the company is using only advertising spend to predict sales,linear regressionis the most appropriate method. Therefore, the correct answer isB.
NEW QUESTION # 33
A nonprofit organization is asking for donations. It hopes to design an email campaign that will ensure it receives at least $50,000. The campaign will reach 10,000 donors and receive donations with a mean of $10 and a standard deviation of $5.
Which measure should be used to determine the probability of the campaign receiving $50,000?
Answer: D
Explanation:
To determine the probability of achieving a specific monetary threshold, data-driven decision making relies on standardization using the z-score. A z-score measures how many standard deviations a value is from the mean and allows analysts to calculate probabilities using the normal distribution.
In this scenario, the nonprofit wants to assess the likelihood that total donations will reach at least $50,000 given a known mean and standard deviation. The z-score enables conversion of the donation target into a standardized value, which can then be evaluated using probability tables or statistical software.
R-squared measures model fit in regression, the t-statistic is used in hypothesis testing, and the median does not support probability calculations. Therefore, the appropriate measure for determining probability in this context is thez-score, making optionDcorrect.
NEW QUESTION # 34
A school board has nine voting members. Five members need to be chosen each year for the finance committee. Why should the combination technique be used when selecting committee members?
Answer: C
Explanation:
The combination technique is appropriate when selecting items or people from a group and the order of selection does not matter. In this case, five members are being chosen from nine voting members to serve on the finance committee. What matters is which five individuals are selected, not the sequence in which their names are chosen. Combinations are used precisely for this type of situation because they count unique groups without regard to arrangement. If order did matter, then a permutation approach would be required instead. The options referring to correlation and meeting attendance are unrelated to the mathematical reason for using combinations. This is a straightforward committee-selection problem, which is one of the most common applications of combinations in probability and counting methods. Recognizing whether order matters is the essential step in choosing between combinations and permutations. Since a finance committee is defined by its membership rather than by the order in which members were picked, the correct answer is that the selection order of committee members is not important.
NEW QUESTION # 35
Which use of statistics would apply to employees?
Answer: B
Explanation:
Statistics can be applied to employees and organizations in many ways, but among the choices given, predicting future levels of financial risk is the best fit for a practical statistical use. Organizations often use statistical models to evaluate uncertainty related to staffing, benefits, payroll obligations, productivity changes, turnover, insurance exposure, and broader business performance. These analyses help managers make more informed decisions about budgeting, hiring, workforce planning, and operational resilience. The other options are less directly tied to employee-related statistical application. Influencing vendor prices and comparing wholesale pricing are more related to procurement and market analysis than to employees.
Determining financial interest rates generally falls under financial markets, lending, or macroeconomic policy rather than an employee-centered use of statistics. In a data-driven environment, statistical tools are frequently used to forecast risk and evaluate future scenarios so that organizations can protect resources and plan responsibly. Therefore, predicting future levels of financial risk is the most accurate answer because it reflects a recognized analytical application of statistics within organizational decision-making.
NEW QUESTION # 36
A student is surveying chief executive officers to understand their levels of satisfaction with work-life balance over a period of three years. The student receives responses to a survey with a question regarding how many hours a week each CEO works. Which statistical approach should be used to summarize the data for analysis?
Answer: B
Explanation:
The question asks how to summarize responses about how many hours each CEO works per week. Since hours worked is a numerical variable, a measure of central tendency is appropriate for summarizing the data.
The mean is the standard choice for describing the average number of hours worked across respondents. It provides a single representative value that can be used to understand the general workload pattern in the group. A bell curve is a distribution shape rather than a summary statistic. A scatterplot is a graphical tool used to display relationships between two quantitative variables, not to summarize one variable's central value. The median can also summarize numerical data, especially if there are strong outliers, but the most direct and standard summary for average hours worked is the mean unless the question specifically emphasizes skewness or resistance to outliers. Since the prompt asks for a statistical approach to summarize the data for analysis, the best answer is mean.
NEW QUESTION # 37
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