AZSCI Math & Computational Thinking 2

Question 1

A student develops a computational model to simulate the spread of a virus in a closed school environment.
The model includes variables for transmission rate, recovery rate, and student density.
When running the simulation with an extremely low transmission rate (approaching zero), the model unexpectedly shows a small, persistent number of infections instead of a complete die-off.
Which of the following best describes this scenario?

Accepted Answer

An edge case where the algorithm for calculating new infections fails to handle near-zero inputs correctly.

Answer

A logical flaw in the model's representation of herd immunity.

Answer

A user interface error in displaying the simulation results.

Answer

A limitation of the hardware's floating-point precision.

Question 2

A team of students is using a block-based programming environment to create a computational model of a predator-prey relationship between wolves and rabbits. To ensure their model is robust, they must consider edge cases. Which of the following represents the most critical algorithmic edge case to test?

Accepted Answer

The model's behavior when the initial population of either wolves or rabbits is set to zero.

Answer

The graphical representation of wolves and rabbits on the screen.

Answer

The simulation speed when running on different computers.

Answer

The color-coding used to differentiate between the two species.

Question 3

A scientist is analyzing a large dataset of daily temperatures for a specific city over 50 years to identify climate trends. Which mathematical technique is most appropriate for identifying a long-term pattern of warming while minimizing the effect of seasonal fluctuations and random daily variations?

Accepted Answer

Applying a moving average with a multi-year window to the dataset.

Answer

Calculating the median temperature for each individual year.

Answer

Creating a scatter plot of daily high vs. low temperatures.

Answer

Finding the single highest and lowest temperatures in the entire dataset.

Question 4

When decomposing a complex scientific problem for computational modeling, what is the primary risk of creating a model with an excessive number of variables and interactions (i.e., making it overly complex)?

Accepted Answer

The model becomes computationally 'expensive,' requiring excessive processing power and time, and may obscure the fundamental relationships being investigated.

Answer

The model will run too quickly to observe the results.

Answer

The model will be unable to incorporate real-world data.

Answer

The model's output will be limited to a simple bar graph.

Question 5

A student is designing an algorithm to control a rover on a distant planet. The rover must navigate from a starting point to a target, avoiding obstacles. The student's algorithm uses a 'left-wall' following strategy. In which of the following scenarios would this specific algorithm most likely fail to find the target, even if a clear path exists?

Accepted Answer

A maze where the target is in the center, surrounded by a circular, detached wall.

Answer

A wide, open plain with no obstacles.

Answer

A single, large crater that must be circumnavigated.

Answer

A narrow canyon leading directly to the target.

Question 6

Students are analyzing a public health dataset to understand the relationship between vaccination rates and disease incidence in different counties. They create a scatter plot and notice one county has a very high vaccination rate but also an unusually high disease incidence, making it a significant outlier. What is the most appropriate next step in their computational analysis?

Accepted Answer

Investigate the outlier for potential confounding variables or special circumstances before drawing conclusions.

Answer

Immediately delete the outlier from the dataset to create a cleaner trend line.

Answer

Conclude that vaccinations are ineffective based on this single data point.

Answer

Assume the data for the outlier is an error and replace it with the average of other counties.