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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Predictive Analytics & Regression | 20% | - Interpreting coefficients, R-squared, significance - Forecasting & trend analysis - Simple & multiple linear regression |
| Topic 2: Statistical Concepts & Descriptive Analytics | 25% | - Measures of central tendency, dispersion, distribution - Data types, measurement scales, sampling methods - Data visualization: charts, graphs, dashboards |
| 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: Decision Models & Prescriptive Analytics | 15% | - Decision trees, payoff matrices, expected value - Quality & process improvement tools - Optimization, sensitivity analysis |
| Topic 5: Probability & Statistical Inference | 20% | - Probability rules, distributions, expected value - Hypothesis testing, p-values, confidence intervals - Correlation vs. causation |
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NEW QUESTION # 107
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 # 108
Research data indicate 95% confidence in a study in which subjects who were shown a product advertisement exhibited brand awareness compared to a control group who did not see the advertisement.
What can be concluded from this study?
Answer: A
NEW QUESTION # 109
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: B
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 # 110
A political ballot gives voters the option to vote for one of three candidates. Eight voters cast their ballots.
Which statistical rule should be used to determine the possible voting outcomes?
Answer: C
Explanation:
Themultiplication principleis used to determine the number of possible outcomes when multiple independent choices occur in sequence. In data-driven decision making and probability theory, this rule applies when each event has a fixed number of outcomes and each outcome is independent of the others.
In this scenario, each of the eight voters can independently choose one of three candidates. The total number of possible voting outcomes is calculated by multiplying the number of choices available for each voter.
Because the voters act independently and order matters in counting outcomes, the multiplication principle is the correct method.
Conditional probability applies when outcomes depend on prior events, Bayes' theorem updates probabilities based on new information, and combinations are used when order does not matter. None of these fit the structure of this problem.
Therefore, the correct answer isA, multiplication principle.
NEW QUESTION # 111
Why are experiments conducted using random sample populations?
Answer: C
Explanation:
Experiments and studies commonly use random samples because observing an entire population is often too difficult, costly, time-consuming, or impractical. In most real-world settings, researchers cannot collect data from every individual, item, or event of interest. A properly selected random sample allows them to estimate population characteristics with a manageable amount of effort while still preserving the ability to make statistical inferences. Random sampling improves representativeness and reduces selection bias, but it does not guarantee total elimination of bias. That is why the option claiming bias elimination is incorrect.
Likewise, the issue is not mainly about outliers or software cost. The main reason for using random samples is feasibility combined with inferential validity. With sound sampling methods, researchers can use probability theory to generalize findings from the sample to the broader population and estimate the degree of uncertainty in those conclusions. Therefore, the strongest and most accurate answer is that studying the entire population is difficult and impractical, making random sampling the preferred and efficient alternative.
NEW QUESTION # 112
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