Lesson OT3.1-OT3.5
OT3.1-OT3.5 Mathematical modelling Quiz: AQA Further Maths, Unit 1
20 questions
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Lesson OT3.1-OT3.5, Mathematical modelling: 20 multiple choice questions for the AQA Further Maths (7367), Unit 1: Overarching themes, written with Revision Ninja.
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The 20 questions
-
What is a modelling assumption?
- A simplifying statement about a situation that makes the mathematics manageable
- A measurement taken directly from real data, used without any simplifying step at all
- A proven fact about the real situation that needs no testing or checking against data
- A value that is always exact and never needs to be estimated or rounded in the model
-
Which of these is a reason to refine a mathematical model?
- It has fewer equations than the original model
- Its predictions differ noticeably from observed data
- It was written by a well-known mathematician
- It uses decimals rather than fractions
-
In the model P = P0 e^(kt), what does P0 represent?
- The initial value of P when t = 0
- The growth rate per unit time
- The value P approaches as t tends to infinity
- The time at which P doubles
-
Which statement about the modelling cycle is correct?
- A model is correct if its mathematics is elegant and its notation is consistent throughout
- A model should never be changed once it has been written, even if its outputs disagree with data
- Outputs of a model need no interpretation in context because the numbers speak for themselves
- A model can be refined by comparing its outputs with observed situations
-
Which statement is a modelling assumption for a particle projected from the ground?
- The particle is projected vertically upwards from the ground with no sideways motion
- The launch speed is fixed at 9.8 m/s for every projectile in the experiment
- Air resistance is negligible and the particle is treated as a point
- The particle has a fixed mass of 2 kg, which is measured before the launch takes place
-
A population is modelled by P = 200 x 1.1^t. After how many whole years does the model first predict more than 400?
- 10 years, since 1.1^10 = 2, so the population doubles every ten years
- 7 years, since P(7) is exactly 400 and the model then reaches its limit
- 5 years, since 1.1^5 = 2, so the population has doubled by year five
- 8 years, since P(7) is about 390 and P(8) is about 429
-
In the cost model C = 500 + 12n for n items made, what does 500 represent?
- The number of items made, which is the variable n in the cost model
- The total revenue from sales, which the model shows as a separate term
- Fixed costs that do not depend on the number of items made
- The cost of each individual item made, which is the coefficient of n in the model
-
A particle's velocity is modelled by v = 20 - 4t for 0 <= t <= 5. What is its velocity at t = 5 according to the model?
- -4
- 20
- 5
- 0
-
A linear model predicts temperature T = 2t + 15. At t = 10 the observed temperature is 33. Which is correct?
- The model predicts 35, an underestimate of 2 degrees
- The model predicts 33, an exact match
- The model predicts 35, an overestimate of 2 degrees
- The model predicts 25, an underestimate of 8 degrees
-
A cooling model is T = 20 + 60e^(-0.1t). What is the long-run temperature as t tends to infinity?
- 20 degrees
- 60 degrees
- 0 degrees
- 80 degrees
-
Which assumption underlies a model with a constant growth rate for a population?
- The population decreases over time
- The population is always a whole number
- The growth rate stays the same over the whole period
- The growth rate changes randomly each year
-
A car moves at a constant speed of 25 m/s according to the model distance = speed x time. How far does it travel in 12 seconds?
- 37 m
- 250 m
- 300 m
- 312 m
-
A model predicts 42 for a quantity, while a refined model that includes air resistance predicts 37. Why is the refined model preferable?
- It contains more terms, so it must be more accurate than the simpler model
- It removes an unrealistic assumption and so fits the situation more closely
- It is easier to solve by hand, which matters more than accuracy in any model
- It gives a larger value, which is always safer to use in a practical decision
-
A model N = 1000 e^(0.4t) describes bacteria. Using ln 10 = 2.303, roughly when does N reach 10000?
- About 2.3 time units
- About 5.8 time units
- About 25 time units
- About 10 time units
-
Which statement best evaluates a population model that gives negative numbers of people for some values of t?
- Negative outputs are always the result of a calculation error
- Negative outputs show that the population is growing
- The model is inappropriate for those values, so it needs refinement
- The model is perfect because the mathematics is correct
-
A model assumes a die is fair, but the die is loaded. Which statement is correct?
- The model's probabilities may be wrong, so its predictions should be checked against data
- The model is correct because dice are generally fair and the assumption is standard
- The model must be discarded because probability cannot be used in any real situation
- A loaded die makes no difference to any prediction that the model makes at all
-
A tank's depth is modelled by h(t) = 2 + 0.5t for 0 <= t <= 8. What is the largest depth the model can validly predict?
- 10
- 8
- 2
- 6
-
A logistic model N(t) = 500 / (1 + 4e^(-0.5t)) describes growth. What is the limiting value of N?
- 2000
- 4
- 500
- 125
-
A sample decays to half its mass in 10 years under the model M = M0 e^(-kt). What is k?
- k = 0.5
- k = 10 / ln 2, about 14.4
- k = 0.1
- k = ln 2 / 10, about 0.0693
-
A model P = 50 + 3t^2 for population, t >= 0, is claimed to show growth forever. What is the main weakness?
- It is correct because it has the right degree and matches the observed growth shape
- It is wrong because t^2 cannot be used for values of t that are non-negative
- It ignores limits such as resources, so long-term predictions may be unrealistic
- It fails because the constant 50 is a fixed term that stops it growing at all
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