Answer:
5
Step-by-step explanation:
f(p) where p is the price in thousands. f(250) means the average number of days before being sold for $250,000. Lets take a look at the answers and see which fits the best:
1. The house sold for $250,000. (This is what the 250 stands for, but we need to find what f(250) means and not just 250)
2. The house stayed on the market for an average of 250 days before being sold. (Nope, not even close)
3. This is the average number of days the house stayed on the market before being sold for $250,000. (Yes! This seems right, f(250) is the average number of days before being sold for $250,000)
4. The house sold on the market for $250,000 and stayed on the market for an average of 250 days before being sold. (Nope, we are not told anywhere that it takes 250 days to be sold)
This means that our answer has to be 3) This is the average number of days the house stayed on the market before being sold for $250,000.
I hope I've helped! :)
Answer:
A.
Step-by-step explanation:
We have x in exponent, so it is an exponential function.
Exponent is negative, so is is an exponential decay.
Answer:
C) The Spearman correlation results should be reported because at least one of the variables does not meet the distribution assumption required to use Pearson correlation.
Explanation:
The following multiple choice responses are provided to complete the question:
A) The Pearson correlation results should be reported because it shows a stronger correlation with a smaller p-value (more significant).
B) The Pearson correlation results should be reported because the two variables are normally distributed.
C) The Spearman correlation results should be reported because at least one of the variables does not meet the distribution assumption required to use Pearson correlation.
D) The Spearman correlation results should be reported because the p-value is closer to 0.0556.
Further Explanation:
A count variable is discrete because it consists of non-negative integers. The number of polyps variable is therefore a count variable and will most likely not be normally distributed. Normality of variables is one of the assumptions required to use Pearson correlation, however, Spearman's correlation does not rest upon an assumption of normality. Therefore, the Spearman correlation would be more appropriate to report because at least one of the variables does not meet the distribution assumption required to use Pearson correlation.
