Descriptive Analysis and Visualization
NCA-ADS · 26 questions
- An emergency-management fusion cell is exploring water-main ages before modeling break risk. Which descriptive approach best fits robust EDA under skewed ages?
- A housing-authority waitlist analytics team must understand missing fields before joining open-data tables. Which EDA focus is most appropriate?
- A courts / clerk e-filing analytics desk is doing EDA on inspection outcomes that include rare fail labels. What descriptive check should come early?
- A library program attendance analytics team finds 311-style queue wait times heavily skewed by a few extreme outliers. Which central-tendency choice fits EDA best?
- A parks and recreation demand desk wants first insights into how complaint types vary by district. Which EDA technique fits best?
- A school-district enrollment analytics team is exploring tables before any model training. Which EDA use best treats analysis as a quality gate?
- A county assessor parcel desk needs interactive views over a very large civic dataset for service-gap exploration. Which visualization approach best fits accelerated descriptive analysis?
- A 311/resident-service analytics team needs leadership to see how response times are distributed. Which visualization best fits that goal?
- A permitting and inspections bureau must brief council on housing vacancy across neighborhoods. Which visualization type best fits that geographic municipal indicator?
- A fire/EMS response-time analytics team is designing severity visuals for inspectors who must read status quickly. Which visualization principle should guide them?
- A public hospital district throughput desk refreshes weekly visual packs for leadership. Which approach best uses accelerated descriptive analysis behind those visuals?
- An elections operations (non-partisan) data team wants to show the relationship between fee amount and processing days. Which plot choice best matches that analysis goal?
- A municipal fleet telematics desk must compare ticket volumes across eight districts for leadership. Which plot selection is most appropriate?
- A solid-waste route optimization analytics team needs to communicate monthly ridership-like demand trends over time. Which plot fits that temporal goal?
- A county social-services case analytics team wants to compare EMS-style response-time distributions across stations. Which plot best supports that goal?
- A city planning zoning analytics team must compare simple budget-share categories for a public report. Which plot guidance should they follow?
- A city open-data portal team wants to know whether a new routing pilot changed mean delay in a statistically meaningful way. Which approach fits Domain 4 hypothesis testing?
- A county public-health analytics team obtains a small p-value comparing two outreach strategies. How should they treat statistical significance responsibly?
- A transit authority ridership desk plans a t-test on heavily skewed fine amounts between two periods. What should they do before trusting the test?
- A water-utility sensor analytics team wants to test whether categorical complaint mix changed after a policy update. Which significance approach fits best?
- An emergency-management fusion cell must present a pilot’s effect size to council with more than a bare p-value. Which reporting practice best fits?
- A housing-authority waitlist analytics team sees park maintenance tickets surge each summer. How should they interpret that pattern?
- A courts / clerk e-filing analytics desk notices rainfall peaks lining up with storm-drain complaint surges. What interpretation is most appropriate?
- A library program attendance analytics team finds one district's outliers pull the citywide average attendance misleadingly high. What should they do when interpreting the pattern?
- A parks and recreation demand desk sees poverty rate correlating with longer service delays. How should they present that relationship?
- A school-district enrollment analytics team notices a sharp step-change in e-filing volumes right after a new system go-live. How should they interpret the pattern?