First you need to combine like terms.
9x + 11y + 13
A coefficient is the number that comes before the variable (which is y).
The coefficient for y is 11.
Constants are the numbers that do not have variables attached to them.
The constant is 13.
Hope this helps!
Answer:
200 trucks
Step-by-step explanation:
There's about 15 trucks in the 2nd row from the right. It looks to be about 1/2 the size of the rows to the left of it.
So based on that, I can assume, there are about 30 trucks in each of the 5 long rows, and both of the short rows would make up about another 30 trucks total. There are various trucks parked along the perimeter or between rows, so I estimated there would be about 20 of those based on 3 per row.
30 x 5 = 150 +30 = 180 + 20 = 200
2√50 × 3√32 × 4√18
=2(5√2) × 3(4√2)× 4(3√2)
=2(5)(2)(3)(4)(4)(3√2)
=2880√2
the anwser is 104 because u subrtacted
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.
