Use the rules of logarithm:
1. log(x)+log(y)=log(xy)
log(x)-log(y)=log(x/y)
2. k*log(x) = log(x^k)
log(x)/k = log(x^(1/k))
<span>log(2z)+2log(2x)+4log(9y)+12log(9x)−2log(2y)
=</span>log(2z)+log(4x^2)+log(9^4y^4)+log(9^12x^12)−log(4y^2)
=log(2z)+log(4x^2)+log(6561y^4)+log(282429536481x^12)−log(4y^2)
=log(59296646043258912 * x^14 * y^6 * z)
Answer:
The circumference is 9 or approximately 28.26 inches.
Step-by-step explanation:
To calculate the circumference of a circle, multiply the diameter of the circle with π (pi). The circumference can also be calculated by multiplying 2×radius with pi (π=3.14).
<h3>
Answer: 3.67 centimeters approximately</h3>
Use the law of sines to get this answer
b/sin(B) = c/sin(C)
c/sin(C) = b/sin(B)
c/sin(60) = 3/sin(45)
c = sin(60)*( 3/sin(45) )
c = 3.6742346 approximately
c = 3.67 rounding to nearest hundredth
Make sure your calculator is in degree mode.
Answer:
Solution-
We know that,
Residual value = Given value - Predicted value
The table for residual values is shown below,
Plotting a graph, by taking the residual values on ordinate and values of given x on abscissa, a random pattern is obtained where the points are evenly distributed about x-axis.
We know that,
If the points in a residual plot are randomly dispersed around the horizontal or x-axis, a linear regression model is appropriate for the data. Otherwise, a non-linear model is more appropriate.
As, in this case the points are distributed randomly around x-axis, so the residual plot show that the line of regression is best fit for the data set.
Hope this helps!
Step-by-step explanation:
