# engineering estimations &approximations Flashcards Preview

## EGG 101 > engineering estimations &approximations > Flashcards

Flashcards in engineering estimations &approximations Deck (11)
1
Q

measurement

A

Measurement is the comparison with a standard.
Measurements are made using Analog and Digital
methods

2
Q

analog measurement

A

Humans perceive their surroundings as a continuous
transmission of information. This non‐stop stream of information is defined as

3
Q

digital measurement

A

Digital information is an estimation of real world
 The process of obtaining digital information is known

4
Q

analog v digital

A

analog is more accurate, digital is easier to manipulate

5
Q

taking measurements

A

Engineering requires measurements to be made
concerning the physical qualities that influence a
design solution.
 One cannot assume that a measurement is exact.
 The use of Significant Figures provides a way of
showing how “good” a measured value is.

6
Q

significant figure/digit

A

Constants & Conversion Factors
 Considered an exact value.
 Exact values have an infinite () number of
significant digits.
 Will not influence the Significant Digit count of a

7
Q

accuracy

A

Accuracy is the closeness of an observation or

measurement to its true value.

8
Q

precision

A

the quality or state of being precise: exactness

9
Q

systematic error

A

a type of error that deviates by a fixed amount from the true value of measurement, all measuremnts are prone to systematic errors.because systematic error is fixed over the range of the measurement it is often referred to as a bias

10
Q

sources of systematic error

A

uncalibrated measurement device (easy to correct), environmental changes which interfere with the measurement process (difficult to identify and correct), imperfect of incorrect method of taking the measurement

11
Q

random error

A

a type of error that adds variability to the measurement but does not affect average performance for the group, random error is the result of uncontrolled factors affecting the measurement across the sample, referred to as measurement noise