Answer:
C = 0.5t + 12. Independent variable is t and the dependent variable is C.
Step-by-step explanation:
$12 is constant, and then $0.50 is multiplied to the amount of toppings (t). So C= 0.5t + 12 and the cost is dependent on the amount of toppings.
Answer:
And the expected value for a vector of zeros and the covariance matrix is given by:
So we can see that the error terms not have a variance of 0. We can't assume that the errors are assumed to have an increasing mean, and we other property is that the errors are assumed independent and following a normal distribution so then the best option for this case would be:
The regression model assumes the errors are normally distributed.
Step-by-step explanation:
Assuming that we have n observations from a dependent variable Y , given by
And for each observation of Y we have an independent variable X, given by
We can write a linear model on this way:
Where i a matrix for the error random variables, and for this case we can find the error ter like this:
And the expected value for a vector of zeros and the covariance matrix is given by:
So we can see that the error terms not have a variance of 0. We can't assume that the errors are assumed to have an increasing mean, and we other property is that the errors are assumed independent and following a normal distribution so then the best option for this case would be:
The regression model assumes the errors are normally distributed.
BC= 8 cm
The measure of angle C is 90
Cos B = 8/15
Sin C = 1
Tan C = 15/8