In 1967, New Zealander Burt Munro set the world record for an Indian motorcycle, on the Bonneville Salt Flats in Utah, of 183.58 mi/h. The one-way course was 5.00 mi long. Acceleration rates are often described by the time it takes to reach 60.0 mi/h from rest. If this time was 4.00 s, and Burt accelerated at this rate until he reached his maximum speed, how long did it take Burt to complete the course?
Solution:
There are two parts to the race: an acceleration part and a constant speed part.
For the acceleration part:
We are given the following values: v_0=0 \ \text{mph} ; v_f=60 \ \text{mph}; and \Delta t=4.00 \ \text{s} .
First, we need to determine how long (both in distance and time) it takes the motorcycle to finish accelerating. During acceleration, the value of the acceleration is given by
a=\frac{60\:\text{mph}}{4\:\text{s}}
To compute for the time it takes to reach its maximum velocity, we are going to use the formula
v_f=v_0+at
Solving for time t in terms of the other variables
t=\frac{v_f-v_0}{a}
Substituting the given values to solve for t_1, the time it takes to accelerate from rest to maximum velocity:
A bicycle racer sprints at the end of a race to clinch a victory. The racer has an initial velocity of 11.5 m/s and accelerates at the rate of 0.500 m/s2 for 7.00 s.
(a) What is his final velocity?
(b) The racer continues at this velocity to the finish line. If he was 300 m from the finish line when he started to accelerate, how much time did he save?
(c) One other racer was 5.00 m ahead when the winner started to accelerate, but he was unable to accelerate, and traveled at 11.8 m/s until the finish line. How far ahead of him (in meters and in seconds) did the winner finish?
Solution:
We are given the following: v_0=11.5 \ \text{m/s} ; a=0.500 \ \text{m/s}^2; and \Delta t=7.00 \ \text{s}.
Part A
To solve for the final velocity, we are going to use the formula
To encourage Elmer’s promising tennis career, his father offers him a prize if he wins (at least) two tennis sets in a row in a three-set series to be played with his father and the club champion alternately: father-champion-father or champion-father-champion, according to Elmer’s choice. The champion is a better player than Elmer’s father. Which series should Elmer choose?
Solution:
Since the champion plays better than the father, it seems reasonable that fewer sets should be played with the champion. On the other hand, the middle set is the key one, because Elmer cannot have two wins in a row without winning the middle one. Let C stand for the champion, F for father, and W and L for win and loss by Elmer. Let f be the probability of Elmer’s winning any set from his father, c the corresponding probability of winning from the champion. The table shows only possible prize-winning sequences together with their probabilities, given independence between sets, for the two choices.
Set with:
Father First
F
C
F
Probability
W
W
W
fcf
W
W
L
fc(1-f)
L
W
W
(1-f)cf
Total
fc(2-f)
Champion First
C
F
C
Probability
W
W
W
cfc
W
W
L
cf(1-c)
L
W
W
(1-c)fc
Total
fc(2-c)
Since Elmer is more likely to best his father than to beat the champion, f is larger than c, and 2-f is smaller than 2-c, and so Elmer should choose CFC. For example, for f=0.8, c=0.4, the chance of winning the prize with FCF is 0.384, that for CFC is 0.512. Thus, the importance of winning the middle game outweighs the disadvantage of playing the champion twice.
Many of us have a tendency to suppose that the higher the expected number of successes, the higher the probability of winning a prize, and often this supposition is useful. But occasionally a problem has special conditions that destroy this reasoning by analogy. In our problem, the expected number of wins under CFC is 2c+f, which is less than the expected number of wins for FCF, 2f+c. In our example with f=0.8 and c=0.4, these means are 1.6 and 2.0 in that order. This opposition of answers gives the problem flavor.
A drawer contains red socks and black socks. When two socks are drawn at random, the probability that both are red is 1/2.
a) How small can the number of socks in the drawer be?
b) How small if the number of black socks is even?
Solution:
Just to set the pattern, let us do a numerical example first. Suppose there were 5 red and 2 black socks; then the probability of the first sock’s being red would be 5/(5+2). If the first were red, the probability of the second’s being red would be 4/(4+2), because one red sock has already been removed. The product of these two numbers is the probability that both socks are red:
This result is close to 1/2, but we need exactly 1/2. Now let us go at the problem algebraically.
Let there be r red and b black socks. The probability of the first sock’s being red is \frac{r}{r+b}; and if the first sock is red, the probability of the second’s being red now that a red has been removed is \frac{r-1}{r+b-1}. Then we require the probability that both are red to be \frac{1}{2}, or
One could just start with b=1 and try successive values of r, then go to b=2 and try again, and so on. That would get the answer quickly. Or we could play along with a little more mathematics. Notice that
And so, 21 is the smallest number of socks when b is even. If we were to go on and ask for further values of r and b so that the probability of two red socks is 1/2, we would be wise to appreciate that this is a problem in the theory of numbers. It happens to lead to a famous result in Diophantine Analysis obtained from Pell’s equation. Try r = 85, b = 35.
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