Never mind, i don't know i'm sorry
A rectangle, is a quadrilateral with all angles at 90°.
a square is a quadrilateral with all equal sides, and right-angles all around.
now, the rectangle as well as the square, have all right-angles, the only difference is that the square has all equal-length sides, whilst a rectangle can have pairs of sides that vary in length.
Thanks for including the graph!
Okay, so -
From examining the graph, we can see that for every minute the number of words increases by 40.
Now, since the x axis (the horizontal thingy kabob at the bottom) is time, and the y axis (the vertical thingy kabob) is the number of words - we can conclude that the answer is B!
Just remember that the value of the y axis is dependent on the value of the x axis. Also, note that x almost always represents time!
Answer:
d. Both I and II are false
Step-by-step explanation:
When there is a high degree of linear correlation between the predictors the errors are found.
The basic objective of the regression model is to separate the dependent and independent variables. So if the variables have high degree of linear correlation then the multi collinearity causes problems or has errors. It is not necessary that multi collinearity must be present with high degree of linear correlation.
For example we have 3 variable of heat length and time. And all of them have a high degree of correlation. With increase in heat and time the length increases . But for multi collinearity with the increase of time and decrease of heat length does not increase. So this causes errors.
y-hat = 135 + 6x + errors
The linear relationship between height and weight is inexact. The deterministic relation in such cases is then modified to allow the inexact relationship between variables and a non deterministic or probabilistic model is obtained which has error which are unknown random errors.
y- hat= a + bXi + ei (i=1,2,3...)
ei are the unknown random errors.
<u><em>So both statements are false.</em></u>
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Wdym by unit rate? I’m guessing u divide 40lb by $24
