Mock Flashcards
Given a bivariate dataset, there is no linear relationship between X and Y when:
a. the slope is larger than 1.
b. the correlation coefficient, r, approaches 0.
c. the y-intercept is lower than -1.
d. the correlation coefficient, r, is equal to unity.
e. both the slope and the y-intercept are equal to zero.
b. the correlation coefficient, r, approaches 0.
Population variability refers to:
a. the variation in the way the margin of security against risks is set.
b. a range of values so defined that there is a specified probability that the value of a parameter lies within it.
c. the range of values that a measurement can take before filtering the experimental signal.
d. how spread out a set of data is. Variability is measured in terms of standard errors/deviations.
e. the way random errors affect the accuracy of a set of experimental data.
d. how spread out a set of data is. Variability is measured in terms of standard errors/deviations.
In a designed experiment, what is the definition of “responses”?
a. Responses are the input values as set by the experimenter.
b. Responses are the numerical values that an independent variable can take during an experiment.
c. The degree to which the result of a measurement, calculation, or specification conforms to the correct value or a standard.
d. The measured outcomes of an experiment.
e. Responses quantify the existing numerical links between factors and levels.
d. The measured outcomes of an experiment.
In an experiment, what are the “uncontrollable factors”?
a. Factors that affect the results from an experiment and are difficult to be controlled.
b. Factors that result in an un-expected and sudden increase of the magnitude of the experimental variables being monitored.
c. The variables in an experiment that could have the most significant impact on the outcome.
d. The un-expected behaviour of a technician during testing.
e. Factors that result in a very loud noise during testing.
a. Factors that affect the results from an experiment and are difficult to be controlled.
Question 5. Why should good experiments be always comparative?
a. Because if you run comparative experiments you can always control them from a distance by using a suitable Internet interface.
b. Because the results from comparative experiments can always be adjusted a posteriori to compensate those errors that are due to experimental noise.
c. Because you can always design comparative experiments so that the magnitude of the input variables can be changed without altering the outputs.
d. Because if you do not monitor the “no treatment” case by using it for comparison, you have no basis for quantifying the effect of the variables you are
investigating.
e. Because the experimental results from comparative experiments are less scattered than the results from non-comparative experiments.
d. Because if you do not monitor the “no treatment” case by using it for comparison, you have no basis for quantifying the effect of the variables you are
investigating.
Question 6. Why should you always replicate your experiments?
a. Because if you generate your experimental results by increasing monotonically the magnitude of the input variables you will not be able to interpolate your data
by using a linear relationship.
b. Because replication quantifies the way random errors affect your experimental results.
c. Because by replicating your experimental measurements you can generate results that fully comply with the recommendations of the codes of practice.
d. Because with replicated measurements we can characterise the variability within measurements and compare to that between measurements.
e. Because by replicating your experimental measurements you can investigate a phenomenon through a circular process of action, conceptualization and evaluation.
d. Because with replicated measurements we can characterise the variability within measurements and compare to that between measurements.
In the design of experiments ambit, what is “randomization”?
a. Randomization is a deliberate process designed to eliminate potential biases from the conclusions.
b. Randomization involves an experimental process where one variable stops another variable from increasing its magnitude.
c. Randomization is a mathematical process we use to adjust a posteriori the experimental results being generated.
d. Randomization means subdividing an experiment into a number of sub- experiments.
e. The chief experimental officer determines “randomization” during testing by choosing randomly different technicians to run different experimental trials.
a. Randomization is a deliberate process designed to eliminate potential biases from the conclusions
Question 8. The basic principles of the design of experiments include
a. Measurand, comparator, and randomization.
b. Replication, sensor, and reference.
c. Replication, randomization, and stratification (or blocking).
d. Replication, randomization, and sensor.
e. Connectors, transducer, and fuses.
c. Replication, randomization, and stratification (or blocking).
Question 9. In metrology, what is the definition of “precision”?
a. Precision is the degree of agreement of the measured quantity with its true magnitude.
b. Precision indicates quality of measurement in terms of reproducibility, without giving any assurance that the measurement is correct.
c. Precision is the degree of repetitiveness of the measuring process.
d. The ability of the measuring instrument to repeat the same results during the act of measurements for the same quantity is known as precision.
e. Precision is about the way a random sample is extracted from the population of interest.
c. Precision is the degree of repetitiveness of the measuring process.
Question 10. In metrology, what is the definition of static calibration?
a. The calibration process that is done while post-processing of the experimental results being generated.
b. Static calibration quantifies the mistakes that are made by the laboratory technicians when they run experiments.
c. With reference to a transducer, static calibration is used to adjust that data acquisition rate.
d. Static calibration is defined as the difference between the indicated value and the true value of the quantity being measured.
e. If the values of the variable involved remain constant (i.e., it is not time dependent) while calibrating a given instrument, this type of calibration is known as static calibration
e. If the values of the variable involved remain constant (i.e., it is not time dependent) while calibrating a given instrument, this type of calibration is known as static calibration
Question 11. What is the definition of “random errors”?
a. Random errors quantify the ability of an instrument to return to the zero reading after the input signal reaches its maximum value.
b. Random errors provide a measure of random deviations when measurements of a physical quantity are carried out repeatedly.
c. Random errors quantify the ability of an instrument to sense the input signal and transform it into its analogous signal.
d. Random errors quantify the degree to which a measurement system indicates the changes in the measured quantity without any dynamic error.
e. Random errors quantify the smallest change in a physical property that an instrument can measure.
b. Random errors provide a measure of random deviations when measurements of a physical quantity are carried out repeatedly.
