Y = m x + b , where m is the slope. The slope is the rise over the run or the change in x ( rooms cleaned ) over the change in y ( cost ).
125 = m * 1 + b
175 = m * 2 + b
-----------------------
b = 125 - m
175 = 2 m + 125 - m
m = 175 - 125
m = 50 ( the rate of change ), b = 75
The formula is: y = 50 x + 75
It means that the starting cost will be $75 and that for every room cleaned, the cost will rise for $50.
1 yard = 3 feet, so we would do 3×84, which is 252.
There are 252 feet in 84 yards.
Nothing just lay in bed all day on my phone-
When calculating correlation and regression both sets of data must be Statistical.
According to the statement
we have to find the type of data when we calculate the correlation and regression both sets.
so, The difference between these two statistical measurements is that correlation measures the degree of a relationship between two variables (x and y), whereas regression is how one variable affects another.
And when we calculate both then data sets must be a statistical data. because correlation summarizing direct relationship between two variables and regression predict or explain numeric response. So, without statistical data this is not possible to calculate correlation and regression both sets.
so, When calculating correlation and regression both sets of data must be Statistical.
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Answer:
- 0.9503 ; r is not statistically significant ; 0.9031
Step-by-step explanation:
Given the following :
Age (X) :
37
41
57
65
73
Bone density (Y)
355
345
340
315
310
Using the pearson R value calculator :
The r value of the data % - 0.9503.
This value depicts a very strong negative correlation between age and density of bone.
Using the pearson R calculator to obtain the P- value, the P value obtained is .01332 and hence the r is not significant at P < 0.01.
The Coefficient of determination R^2 can be obtained by getting the square value of R
R^2 = - 0.9503^2
R^2 = 0.90307009
R^2 = 0.9031
