You've started an internship at the major hospital in your city. Your boss gave you ten minutes of training on the data warehouse that you have access to. She then asked you to see if there is any correlation between treatments and day of the week. To do this, you will be doing:

Question

BlackTom AI · Accepted Answer

Data mining involves extracting patterns, correlations, and insights from large datasets, so it directly applies to finding whether treatments vary by day of the week.

Relevant concepts:
- Data mining: discovery of patterns/associations (e.g., association rules, clustering, classification, statistical tests).
- Transaction processing: records routine operations (OLTP), not used for discovering correlations.
- Goal-seeking: solving for inputs that achieve a target output (what-if/backsolving), not exploratory pattern discovery.
- Exception reporting: flags records that violate norms or thresholds (alerts), not broad pattern discovery.

Step-by-step reasoning:
1. Identify the analytical objective: determine whether treatment type/frequency is correlated with day-of-week (pattern discovery).
2. Obtain and prepare data from the warehouse: select variables (treatment id, date → day-of-week), clean duplicates/missing values, aggregate counts by day.
3. Choose data-mining/statistical methods: e.g., contingency tables with chi-square test for independence, association-rule mining to find rules like {day = Monday} → {treatment = X} with support/confidence, or clustering to see day-based groupings.
4. Execute and evaluate: compute test statistics, p-values, or rule metrics and interpret whether patterns are statistically or practically significant.

Illustrative calculation (small example): suppose Treatment A counts: Mon–Fri = 120, Weekend = 30; Treatment B: Mon–Fri = 80, Weekend = 70. Contingency table totals: Mon–Fri 200, Weekend 100, Treatments total 200 each. Expected count for Treatment A on Weekend = (200 * 100)/300 = 66.67. Chi-square term = (30−66.67)^2/66.67 ≈ 20.37. Summing all terms yields a high chi-square → reject independence → evidence of association. This is a standard data-mining/statistical approach.

Why the other options are incorrect:
- Transaction processing: stores/handles day-to-day transactions, not pattern discovery.
- Goal-seeking: determines inputs to meet targets, not find correlations.
- Exception reporting: surfaces outliers/exceptions, not general correlation analysis.

Therefore, the correct answer is data mining, which matches the provided answer.

You've started an internship at the major hospital in your city. Your boss gave you ten minutes of training on the data warehouse that you have access to. She then asked you to see if there is any correlation between treatments and day of the week. To do this, you will be doing:单项选择题

类似问题

Which statement about data mining is NOT true?

While data mining has little impact in increasing sales in a firm, it has proven to be very beneficial in uncovering patterns such as credit card fraud.

以下哪些操作属于数据挖掘？ Which of the following operations belong to data mining?

Data mining involves the extraction of hidden predictive information in large databases through statistical analysis.

_为用户提供了关于发生情况的视角，而_则探讨了为什么会发生。

Most frequently sold items after grouping customers by age group. Is it a data mining task?

Grouping customers by both age group and purchase time across multiple years. Is it a data mining task?

An arithmetic average of daily temperatures over a month. Is it a data mining task?

更多留学生实用工具

智能学习助手

风格化写作助手

论文查重助手

文献引用助手

课堂转译助手

课堂笔记助手

Quiz搜索助手

学校历年真题

智能刷题助手

智能匹配练习

希望你的学习变得更简单