Answer:
my answer would be that
x = 17.91cm
(i'm not sure about it either but it's worth a try) !!
Step-by-step explanation:
so first off, using the equation given,
" c² = a² + b² — 2ab cos C "
we substitute the values in as,
a = 16
b = 30
then for C is the angle given, which is 30°
so the equation is now,
c² = (16)² + (30)² — 2(16)(30) cos 30°
now, you solve the two squared numbers and the back equation, also known as " 2ab cos C " with your scientific calculator.
so it now equals to,
c² = 256 + 900 — 960(0.87)
c² = 320.8
at last, when you have " c² = 320.8 " ,
remember to square root the answer so you have a smaller value.
so,
c equals to
your final answer for the x value will be 17.91
(i hope this helps!)
please refer to this image
please don't report this answer if it is wrong
but if its correct so please mark me as brainlist
"The total number of stamps is 35" is the statement among the following choices given in the question that is correct. The correct option among all the options that are given in the question is the third option or the penultimate option. I hope that this is the answer that has actually come to your great help.
<u>Answer-</u>
<em>The least squares regression equation using the school year (in number of years after 2000) for the input variable and the average cost (in thousands of dollars) for the output variable is "y=0.937x+12.765" .</em>
<u>Solution-</u>
The independent variable / input variable= x = Number of years after 2000 ( = year-2000)
The dependent variable / output variable = y = Average cost in thousands of dollars
(The table has been attached herewith.)
To find the regression equation for a group of (x,y) points,
We have to calculate the slope and y-intercept, then we can put those values in the equation y = mx + c ( Slope - Intercept formula)
We know that,
Putting the values from the table,
( ∵ Instead of 150,894 we have to put 150.894 as we have find the line for year and thousands of dollars )
Now, for the y-intercept,
Putting the values,
Now, putting the values of c and m, in the Slope-Intercept formula,
