Final answer:
The question concerns matching data analytics tests with appropriate test approaches in a business test plan, analyzing data, and verifying results through methods such as a Goodness-of-Fit Test and Matched or Paired Samples. Analysis is essential for ensuring the accuracy and relevance of the data to the test objective.
Step-by-step explanation:
The question asks about matching specific data analytics tests to test approaches in the context of a test plan. This involves various strategies to analyze data effectively to ensure accurate results that can inform decision-making processes. For example, a Goodness-of-Fit Test may be used to determine how well sample data fits a theoretical distribution.
Furthermore, the Candidate Analysis and Testing section suggests that after gathering relevant data, replication is crucial for verifying results. Tests such as personality assessments, IQ tests, integrity tests, and physical tests like drug testing can measure various candidate qualities and fit for a job role. Assuring a match between test results and job performance is vital.
In the context of a software study, a Matched or Paired Samples approach is highlighted where a software patch's effectiveness is tested by comparing system failures before and after the patch is applied. This requires a normal distribution of the differences for the test at a 1 percent significance level.
Finally, engaging in analysis is a critical skill across disciplines, not only in business. Analysis involves breaking down data or texts into their constituent parts and making interpretive claims.