Sampling Methods Flashcards
7 cards from real NETTCP practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Sampling Methods flashcards as text
When sampling hot mix asphalt (HMA) from a truck, which location in the load is generally AVOIDED to reduce segregation bias?
Answer: Top surface directly beneath the chute
Material directly beneath the truck's discharge chute tends to be coarser due to segregation and is avoided when sampling.
What AASHTO standard governs the sampling of aggregates for road and bridge construction?
Answer: AASHTO T 2
AASHTO T 2 is the standard method of sampling aggregates.
A technician needs a 5 kg sample but the field sample yielded 20 kg. What process reduces the sample to the required size?
Answer: Quartering or splitting
Mechanical splitting or the quartering method is used to reduce a large field sample to a representative test sample.
For soils testing on a highway project, a random sampling plan is preferred over convenience sampling primarily because it:
Answer: Eliminates operator bias in sample location selection
Random sampling removes operator bias, ensuring that every location has an equal probability of being selected.
Which equipment is used for mechanical sample splitting of fine-grained soils and aggregates to ensure representative reduction?
Answer: Riffle splitter (sample splitter)
A riffle splitter divides a sample into two equal halves by directing material alternately into opposite chutes.
When collecting a concrete sample from a ready-mix truck, AASHTO R 60 requires discarding the first portion of discharge. How much is typically discarded?
Answer: First 0.25 cubic yards
The first approximately 0.25 cubic yards of discharge is discarded because it may not be representative of the full load.
In stratified random sampling of a pavement project, the roadway is divided into equal sections and samples are taken randomly within each. What is the primary advantage of this approach?
Answer: It ensures proportional coverage across the full project length
Stratified random sampling ensures every portion of the project is represented, avoiding gaps that pure random sampling might miss.