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MIS 2502 Final Exam Q&A: Decision Trees, Clustering, and Data Mining, Exams of Medicine

University of Maryland - BaltimoreMedicine

A compilation of questions and verified answers related to mis 2502, focusing on key concepts such as decision trees, clustering, and association rule mining. It covers various aspects of data analysis, including the uses of decision trees in predicting customer behavior, the application of clustering in customer segmentation, and the role of association rule mining in identifying product relationships. Additionally, it explains the differences between olap and data mining, the functions of r and rstudio, and essential statistical concepts like p-value and hypothesis testing. The document also delves into cluster analysis, k-means, and market basket analysis, offering insights into cohesion, separation, support, confidence, and lift. It serves as a valuable resource for students preparing for exams or seeking a concise review of these topics.

Typology: Exams

2025/2026

Available from 12/23/2025

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MIS 2502 FINAL UPDATED Questions and
Verified Answers
Decision Tree - CORRECT ANS W E R S ⬛ ⬛
-used to classify data according to a pre-defined
outcome
-Based on characteristics of that data
Decision Tree Uses - CORRECT ANSW E R S ⬛ ⬛
-Predict whether a customer should receive a
loan or will default on a loan
-Flag a credit card as legitimate
-Determine whether an investment will pay off
Clustering - CORRECT ANSW E R S ⬛ ⬛
-Used to determine distinct groups of data
-Based on data across multiple dimensions
Clustering Uses - CORRECT ANSW ER S ⬛ ⬛
-Customer segmentation
-Identifying patient care groups
-Performance of business sectors
Association Rule Mining - CORRECT ANS W E R S ⬛ ⬛
-Find out which events predict the
occurrence of other events
-often used to see which products are bought together
Association Rule Mining Uses - CORRECT ANS W E R S ⬛ ⬛
-What products are bought
together
-Amazon's recommended engine
-Telephone calling patterns
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Download MIS 2502 Final Exam Q&A: Decision Trees, Clustering, and Data Mining and more Exams Medicine in PDF only on Docsity!

MIS 2502 FINAL UPDATED Questions and

Verified Answers

Decision Tree - CORRECT A N S W E R S ⬛⬛-used to classify data according to a pre-defined outcome

  • Based on characteristics of that data Decision Tree Uses - CORRECT A N S W E R S ⬛⬛-Predict whether a customer should receive a loan or will default on a loan
  • Flag a credit card as legitimate
  • Determine whether an investment will pay off Clustering - CORRECT A N S W E R S ⬛⬛-Used to determine distinct groups of data
  • Based on data across multiple dimensions Clustering Uses - CORRECT A N S W E R S ⬛⬛-Customer segmentation
  • Identifying patient care groups
  • Performance of business sectors Association Rule Mining - CORRECT A N S W E R S ⬛⬛-Find out which events predict the occurrence of other events
  • often used to see which products are bought together Association Rule Mining Uses - CORRECT A N S W E R S ⬛⬛-What products are bought together
  • Amazon's recommended engine
  • Telephone calling patterns

Difference between OLAP(Online Analytical Processing and Data Mining) - CORRECT A N S W E R S ⬛⬛-OLAP can tell you what is happening now and what has happened in the past

  • Data Mining can tell you why it is happening and help predict what will happen in the future R - CORRECT A N S W E R S ⬛⬛-the actual programming language and software development platform (base engine) RStudio - CORRECT A N S W E R S ⬛⬛-the integrated development environment of R, requires R to run (pretty face) packages in R - CORRECT A N S W E R S ⬛⬛-They perform data analysis functions, they are add ons Variables - CORRECT A N S W E R S ⬛⬛-containers for data Functions - CORRECT A N S W E R S ⬛⬛- these can accept parameters() and return values, performs an action Syntax to retrieve variable from dataset - CORRECT A N S W E R S ⬛⬛dataSet$tablename P value< or equal to .05 - CORRECT A N S W E R S ⬛⬛reject the null hypothesis, it is statistically significant Pvalue> to .05 - CORRECT A N S W E R S ⬛⬛fail to reject the null hypothesis, it is not statistically significant Classification - CORRECT A N S W E R S ⬛⬛-a statistical method used to determine to what category a new observation belongs
  • classify new cases into known classes

Within-cluster SSE or withinss - CORRECT A N S W E R S ⬛⬛-measures Cohesion, how tightly grouped together each cluster is

  • More clusters will reduce withinss
  • Reducing within-cluster SSE increases Cohesion Between-cluster SSE or betweenss - CORRECT A N S W E R S ⬛⬛-measures Separation, the distance between centroids
  • More clusters will reduce betweenss
  • Redcuing between-cluster SSE decreases separation Favorable cluster sse - CORRECT A N S W E R S ⬛⬛High Cohesion(low withinss) and High Separation (high betweenss) Average value for standardized values - CORRECT A N S W E R S ⬛⬛ 0 Market Basket Analysis - CORRECT A N S W E R S ⬛⬛-what products are bought together and where to place items on grocery shelves Can you have high confidence and low lift? - CORRECT A N S W E R S ⬛⬛Yes, when both X and Y are popular, you'd expect them to show up in the same basket by chance Support - CORRECT A N S W E R S ⬛⬛-fraction of transactions that contains all items in the interest
  • (number of times rule appears in a basket)/total number of baskets Confidence - CORRECT A N S W E R S ⬛⬛strength of an association, measures how often items in Y appear in transactions that contain X
  • support of (x->y)/support of (x)

Lift - CORRECT A N S W E R S ⬛⬛-takes into account how co-occurrence differs from what is expected by chance

  • support of (x->y)/support of (x) * support of (y) Lift>1 - CORRECT A N S W E R S ⬛⬛the occurrence of X->Y together is more likely than what you would expect by random chance (positive association) Lift<1 - CORRECT A N S W E R S ⬛⬛the occurrence of X->Y together is less likely than what you would expect by random chance (negative association) Lift = 1 - CORRECT A N S W E R S ⬛⬛the occurrence of X->Y together is the same as random chance ( No apparent association)