Answer:
2 pounds
Step-by-step explanation:
A Canadian postal code looks like this:
K1A 3B1 .
So you have: letter - digit - letter - digit - letter - digit .
The question doesn't say anything about restrictions on
which letters can be used, or restrictions on repeating letters
or digits within one postal code. So as far as we know, each
letter can be any one of 26, and each digit can be any one of 10.
The total number of possibilities would be
(26·10·26) · (10·26·10) = 17,576,000 .
In the real world, though, (or at least in Canada), Postal codes
don't include the letters D, F, I, O, Q or U, and the
first letter
does not use W or Z. When you work it out with these restrictions,
it means there's a theoretical limit of 7.2 million postal codes.
The practical limit is a bit lower, as Canada Post reserves some
codes for special functions, such as for test or promotional purposes.
One example is the code H0H 0H0 for Santa Claus ! Other special
codes are for sorting mail
bound for destinations outside Canada.
At the present time, there are a little over 830,000 active postal codes.
That's about 12% of the total possibilities, so there are still plenty of codes
left for expansion.
Part A. The correlation coefficient, denotes as R^2, is a measure of how well does the data point correlate with a given model or equation. The closer the R^2 is to 1, the better is the correlation. However, R2=1 is ideal for scatter plots. Using the MS Excel to execute the regression, the data points was fitted to a quadratic equation. The R2=0.9983. From the choices, the closest answer would be 1. But as stated previously, a value of 1 is ideal only. Therefore, the answer is most likely 0.94,
Part B. To determine the slope, the equation would be Δy/Δx. For x=5 and x=10, the slope would be
Slope = (3-1)/(10-5) = 2/5 or 0.4. This is the instantaneous rate of change at the interval of 5 to 10 days.
Part C. The difference between causation and correlation is identifiable if you know the direct relationship between the variables. In this case, the increase in radius is not caused by time. The problem does not state so. But we know from the trend shown on a graph, that there is a correlation between these variables. Therefore, the answer is correlation.