Answer:
D. One
Step-by-step explanation:
A parallelogram will have two sets of equal sides. Since we have that fact, all we need to know are the angles.
A quadrilateral will have a total of 360° in its angles. If only one angle is equal to 90°, then we can do <u>the math</u> to figure out that all the others must be 90° as well. A rectangle is a parallelogram with the opposite sides being parallel and all the angles being 90°. This then answers the question.
"<u>The Math</u>"
-> Keep in mind there will be four angles
-> Once we subtract the first angle of 90°, we will have three angles left. Hence why we divide by 3.
360° - 90° = 270°
270° / 3 = 90° ✓
No. That's only true if x is less than ' 1 ', including anything negative. If x is more than +1, then the square is LESS than the cube.
It's an arithmetic sequence. The first term is 1 and the common difference is 4.
A function of random variables utilized to calculate a parameter of distribution exists as an unbiased estimator.
<h3>What are the parameters of a random variable?</h3>
A function of random variables utilized to calculate a parameter of distribution exists as an unbiased estimator.
An unbiased estimator exists in which the difference between the estimator and the population parameter grows smaller as the sample size grows larger. This simply indicates that an unbiased estimator catches the true population value of the parameter on average, this exists because the mean of its sampling distribution exists the truth.
Also, we comprehend that the bias of an estimator (b) that estimates a parameter (p) exists given by; E(b) - p
Therefore, an unbiased estimator exists as an estimator that contains an expected value that exists equivalent to the parameter i.e the value of its bias exists equivalent to zero.
Generally, in statistical analysis, the sample mean exists as an unbiased estimator of the population mean while the sample variance exists as an unbiased estimator of the population variance.
Therefore, the correct answer is an unbiased estimator.
To learn more about unbiased estimators refer to:
brainly.com/question/22777338
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Answer:
It was good how about you? :D
Step-by-step explanation:
