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WorksheetsPre-Test Module 7B
Total questions: 10
Worksheet time: 8mins
In the formula for estimating the number of replications, the symbol t1-α/2 represents:
Significance level
Square root of replications
T-value at confidence level
Sample standard deviation
T-statistic of the sample mean
According to Hoover and Perry (1990), what is validation in the context of system modeling?
The process of running simulations to observe system behavior
The process of collecting input data from the real system
The process of determining whether the model correctly reflects the conceptual model
The process of determining whether the model is a meaningful and accurate representation of the real system
The process of identifying errors in computer code
The process of determining whether the model correctly reflects the conceptual model and operates as intended, is the definition of ...
Simulation
Verification
Sample system
Validation
Population
Which of the following are verification techniques in system modeling?
Watching the animation
Comparing with other models
Testing against historical data
Running traces
Watch the animation for correct behavior
Without requiring equal sample sizes or equal population variances, the test used to compare the means between two independent groups is …
Normality test
Welch test
ANOVA
Chi-square test
Regression test
In the WIP Template, line lines will be used in the form of a …, which represents each process and is intended to be exported into a CSV file.
Graph
Summary
Table
Formula
Line
Which of the following correctly represents the relationship between error (e) and half-width (hw)?
e = hw
e > hw
e ≠ hw
e < hw
e ≥ hw
The sample standard deviation (s) is calculated to measure the dispersion of the observed data points around the …
Sample mean
Standard deviation
Average
Population
Total
One of the software used in this practicum is …
Stat::Fit
IBM SPSS
AutoCAD
Visual Studio Code
Google Colab
The main reasons why validation and verification are often disregarded in simulation activities are as follows, except…
Overconfidence
Ignorance
Laziness
Time and budget pressures
Focus on model accuracy
