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| Section | Objectives |
|---|---|
| Data Fundamentals and Business Analytics | - Descriptive statistics (mean, median, variance, standard deviation) - Data types and data collection methods |
| Hypothesis Testing | - Null and alternative hypotheses - t-tests, chi-square tests, and significance testing |
| Regression and Correlation Analysis | - Interpreting correlation and causation - Linear regression modeling |
| Probability and Statistical Inference | - Sampling methods and sampling error - Probability concepts and distributions |
| Decision Making Models | - Decision trees and expected value analysis - Risk and uncertainty in decision-making |
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NEW QUESTION # 69
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: B
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 # 70
A hot tub company recently calibrated all its machines during an expensive maintenance cycle performed by an outside company. However, defective pumps with small cracks are being made on the production line. The manager reviews the data about the errors and discovers that more errors occur during the night shift than during the day shift.
Which type of activity is this manager performing?
Answer: A
Explanation:
Quality controlinvolves monitoring, measuring, and analyzing production output to identify defects and variations. In data-driven decision making, quality control focuses on detecting problems after or during production rather than preventing them in advance.
In this scenario, the manager reviews defect data and identifies a pattern indicating more errors during the night shift. This analysis is a classic quality control activity, as it involves examining performance data to detect issues in the production process.
Quality assurance focuses on process design and prevention, while service and underlying activities are not standard quality management classifications. Therefore, the correct answer isD, quality control activity.
NEW QUESTION # 71
Which two characteristics must a researcher consider concerning data quality when ensuring that an analysis is based on a clean data set?
Choose 2 answers.
Answer: A,D
Explanation:
When evaluating whether a data set is clean enough for analysis, a researcher must focus on data quality dimensions that directly affect validity and usefulness. Two important characteristics are uniqueness and relevance. Data elements must be unique to prevent duplicate records from distorting counts, averages, totals, and trend analyses. Duplicate entries can lead to biased results, especially in customer, transaction, or survey data. Relevance is equally important because even accurate data are not helpful if they do not pertain to the question being studied. A clean data set should support the actual purpose of the analysis rather than merely being complete or large. The statement about age is incorrect because timeliness often matters; outdated data may no longer reflect the current environment. The statement that data cannot contain outliers is also too absolute. Outliers may be valid observations and can sometimes reveal important conditions, anomalies, or data-entry problems that require investigation rather than automatic removal. Thus, the best two characteristics are uniqueness and relevance, because both directly support meaningful, accurate, and decision- ready analysis.
NEW QUESTION # 72
Which two tools make it easier to detect an out-of-range error?
Choose 2 answers.
Answer: B,C
Explanation:
Out-of-range errors occur when a data value falls outside the allowable or expected limits for a variable.
Examples include a negative age, a score above the maximum possible value, or a date in an impossible format. The tools most useful for identifying such errors are relational databases and spreadsheets. Relational databases often include validation rules, field constraints, data types, and query capabilities that can detect impossible or invalid entries. For example, a database can restrict a field to numeric values within a set range or flag records that violate defined rules. Spreadsheets can also support error detection through conditional formatting, formulas, filters, data validation, and sorting features that make unusual values easier to spot.
Experimental studies and observational studies are research designs, not data-validation tools. They describe how data are collected, not how errors are detected in stored records. Because the question asks specifically for tools that make out-of-range errors easier to detect, the correct choices are the data-handling tools that support validation and review: relational databases and spreadsheets.
NEW QUESTION # 73
Amusement Park W is in California. Amusement Park X is in Texas. A survey asks 1,000 people living in California if they prefer Amusement Park W or X.
Which problem exists with this survey?
Answer: A
Explanation:
The primary problem with this survey issystematic error, which occurs when the data collection process consistently favors certain outcomes due to flawed design. In data-driven decision making, systematic error arises when a sampling method introduces bias that skews results in a predictable direction.
In this scenario, surveying only people living in California creates a location-based bias. Respondents are far more likely to prefer Amusement Park W because it is geographically closer, more familiar, and more accessible than Amusement Park X in Texas. This bias does not occur randomly; instead, it systematically influences responses toward one option, making the results unreliable for comparing overall preferences between the two parks.
Random error would involve unpredictable variation, which is not the issue here. Measurement bias relates to how questions are asked or measured, and information bias concerns inaccurate or misleading data reporting.
The core issue is thenon-representative sample, which violates the principle of unbiased data collection.
Data-driven decision making emphasizes that valid conclusions require representative samples. Because the survey design inherently favors one outcome, the results cannot be generalized, makingsystematic errorthe correct answer.
NEW QUESTION # 74
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