Answer:
$300
Step-by-step explanation:
Given that:
Derek bought a new car for $32,000;
The original amount of purchase = $32,000
Down payment = $17,000
Remaining amount = Original amount of purchase - Down payment
= $(32000 -17000)
= $ 15,000
Also;
rate of interest per month is 2%
and the Derek is unable to pay his first monthly payment
thus the interest amount is calculated on principal amount
so for the first month interest is calculated on total principal amount
The month interest payment is then calculated as :
= 15,000 × 2%
= 15,000 × 0.02
= $300
Step-by-step explanation:
first your going to break down your total then since you have nine balls of yarn you going to take out the 9.45
Answer:
Green ball. $11
Step-by-step explanation:
Let's see.
15 balls. 7 are red. 6 are green. rest are yellow. That means there are 2 yellow balls.
Since there are more greens than yellows, you have a better chance of getting a green. That means you have a higher chance of getting $11
Answer:
9 Superscript negative 3
Step-by-step explanation:
Answer:
Since the name indicates Minimum Variance Unbiased Estimator-first of all it is a parameter estimator. Secondly, it is an unbiased estimator so that the sample is carried out randomly. I.e. whenever a sample is chosen, there is no personal bias.
Then we can consider more than one sample-based unbiased estimator but sometimes they can vary in variation. But we have always intended to select an estimator that has minimal variance.
Therefore if the unbiased estimator has minimal variation between all unbiased class estimators then it is known as a good estimator.
The advantage of MVUE is that it is impartial and has a minimal variance of all unbiased estimators amongst the groups.
At times we get an estimator such as MLE which is not unbiased because the sample can be personally biased. Now let us assume an instructor needs to find the lowest marks in a physics class. Presume an instructor picks a sample and interprets the lowest possible marks.
Again the mistake could be that the instructor may choose his favorite sample learners because the sample might not be selected randomly. Therefore it is important to select an unbiased estimate with a minimum variance.
