Oakdale is the answer I think
Answer:
If you are <u>traversing squares</u> then 7 different paths can be taken
If you are <u>traversing edges </u> then 36 different paths can be taken
Step-by-step explanation:
I have attached a picture that would describe the grid which is 7 units long.
The solution to the general problem is if you have to take X right steps, and Y down steps then the number of routes is simply the ways of choosing where to take the down (or right) steps. Such that:
Basically its the combination of terms.
In this problem,
If you are <u>traversing squares</u> then there are 6 right steps and 1 down step,
7 C 1 = 7 C 6= 7
If you are <u>traversing edges </u> then there are 7 right steps and 2 down steps:
9 C 2 = 9 C 7= 36
Answer: 5 minutes
Step-by-step explanation:
We know that 1760 yards are in a mile. We can convert the given info into a proportion. 440/75 = 1760/x, where x is the number of seconds it takes to run a mile. Cross-multiply to get 440x = 75*1760. Divide both sides by 440 to get x = 75*4 = 300 seconds. The problem asks for how many minutes so you have to convert 300 seconds to minutes. To do this, we have to divide 300 by 60 to get 5 minutes.
Answer:
The homoskedasticity-only F-statistic and the heteroskedasticity-robust F-statistic typically are different.
Step-by-step explanation:
An F statistic is a value derived by running an ANOVA test or a regression analysis to find out if the means between two populations are significantly different.
The homoskedasticity-only” F-statistic is derived by running two regressions, one under the null hypothesis and one under the alternative hypothesis. If the “unrestricted” model fits sufficiently better, reject the null.
In the first regression, the restricted regression (the null hypothesis) is forced to be true. This is the regression in which all the coefficients are set to zero; the relevant regressors are excluded from the regression. In the second regression, the unrestricted regression, the alternative hypothesis is allowed to be true. If the sum of squared residuals is sufficiently smaller in the unrestricted than the restricted regression, then the test rejects the null hypothesis
The heteroskedasticity-robust F-statistic is built in to STATA (“test” command); this tests all q restrictions at once.
The homoskedasticity-only F-statistic is important historically (and also in practice), and can help intuition, but isn’t valid when there is heteroskedasticity
I tried answering this question but got it wrong. Please ignore this message D:
