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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Probability & Statistical Inference | 20% | - Hypothesis testing, p-values, confidence intervals - Correlation vs. causation - Probability rules, distributions, expected value |
| Topic 2: Predictive Analytics & Regression | 20% | - Interpreting coefficients, R-squared, significance - Forecasting & trend analysis - Simple & multiple linear regression |
| Topic 3: Decision Models & Prescriptive Analytics | 15% | - Optimization, sensitivity analysis - Quality & process improvement tools - Decision trees, payoff matrices, expected value |
| Topic 4: Statistical Concepts & Descriptive Analytics | 25% | - Data visualization: charts, graphs, dashboards - Measures of central tendency, dispersion, distribution - Data types, measurement scales, sampling methods |
| Topic 5: Foundations of Data-Driven Decision Making | 20% | - Role of data in business decisions - Ethics, privacy, and data governance - Types of analytics: descriptive, predictive, prescriptive |
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NEW QUESTION # 109
What is an omission error?
Answer: C
Explanation:
Anomission erroroccurs whencrucial data is missingfrom a dataset, which can significantly compromise the quality of analysis and decision-making. In data-driven decision making, omission errors are a serious concern because missing information can lead to biased results, incorrect interpretations, and flawed conclusions.
Omission errors may arise during data collection, data entry, or data integration processes. For example, failing to record customer demographics, transaction values, or time periods can distort descriptive statistics and weaken predictive models. Unlike inaccuracies, which involve incorrect values, omission errors involve the absence of necessary data altogether.
Outliers represent extreme values and are not omission errors. Similarly, failing to review all data is a process issue rather than a data-quality error definition. Inaccurate data refers to incorrect or erroneous values, not missing ones.
Effective data quality management emphasizes identifying and correcting omission errors through validation rules, completeness checks, and data audits. In data-driven decision making, ensuring that all relevant data is captured is essential for producing reliable insights and supporting sound business decisions. Therefore, the correct answer isD, as an omission error occurs when crucial data is missing.
NEW QUESTION # 110
Which term describes a response that appears the greatest number of times compared to other responses in a survey?
Answer: B
Explanation:
Themodeis the value that appears most frequently in a dataset. In data-driven decision making, it is particularly useful for analyzing categorical or discrete survey data.
The median represents the middle value, the mean is the average, and outliers are extreme values. Because the question asks for the most frequently occurring response, the correct answer isA, mode.
NEW QUESTION # 111
What is the primary goal of Six Sigma?
Answer: B
Explanation:
The primary goal ofSix Sigmais tofoster a commitment to continuous improvementby systematically reducing defects and process variation. In data-driven decision making, Six Sigma uses statistical methods to improve quality, efficiency, and consistency across organizational processes.
Six Sigma emphasizes disciplined problem-solving through data analysis, root-cause identification, and process control. While reducing defects to 3.4 per million opportunities is a hallmark metric, the broader objective is embedding continuous improvement into organizational culture.
SIPOC is a supporting tool, leadership is a contributing factor, and collaborative planning forecasting and replenishment relates to supply chain management, not Six Sigma's core purpose.
Therefore, the correct answer isD.
NEW QUESTION # 112
What is the formula for calculating a simple index number?
Answer: D
Explanation:
Asimple index numberis used in data-driven decision making to measure relative change in a variable over time, commonly prices, quantities, or values. The standard formula for a simple price index compares the value in the current period to a base period and expresses the change as a percentage.
The correct formula is thecurrent price divided by the base year's price, multiplied by 100. This standardization allows analysts and managers to easily interpret changes relative to a reference point. An index value of 100 indicates no change from the base year, values above 100 indicate an increase, and values below 100 indicate a decrease.
This approach is widely used in economic analysis, inflation tracking, and business trend evaluation because it simplifies comparisons across time. Dividing the base year by the current price would reverse interpretation, and omitting multiplication by 100 would fail to express the index in percentage terms.
Therefore, optionAcorrectly represents the formula for calculating a simple index number.
NEW QUESTION # 113
A digital marketing manager wants to determine whether conversion rates from the company's latest email campaign are about the same as the industry average or significantly different. Which statistical concept should be used to measure the data set?
Answer: B
Explanation:
To determine whether the campaign's conversion rates are about the same as the industry average or significantly different, the manager must consider not only the average value but also how much variation exists in the data. Standard deviation is the measure that captures the spread or variability of the data around the mean. This makes it essential when evaluating whether an observed conversion rate is unusually high, unusually low, or within a normal expected range compared with the industry. The mean gives the central average, but by itself it does not show whether a result is significantly different. The median identifies the middle value, which is useful in skewed data but not sufficient for judging statistical difference in this context. A bell curve describes the shape of a normal distribution rather than serving as the core numerical measure needed here. Since the question is about determining whether results differ meaningfully from an average benchmark, standard deviation is the most appropriate concept among the options provided.
NEW QUESTION # 114
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