We use the chi-square distribution when making inferences about a single population variance.
Short Description of Chi-Square Distribution
The continuous probability distribution known as the chi-square distribution. The number of degrees of freedom (k) a chi-square distribution has determines its shape. This type of sampling distribution has a variance of 2k and a mean equal to its number of degrees of freedom (k). The range is of a chi-square distribution is from 0 to ∞.
Variance plays a key role in the analysis of risk and uncertainty. The sample variance, an unbiased estimator of population variance, is expressed by the following formula of core statistic for a sample size 'n' and Y' as the sample mean:
S² = ∑(Yₓ - Y') / (n-1)
The formula, (n-1)S² / σ² has the central chi-square distribution as χ²ₙ₋₁. Here (n-1) represents the degrees of freedom.
Learn more about chi-square distribution here:
brainly.com/question/13857280
#SPJ1
Answer:
option C
Step-by-step explanation:
if a function is linear then we know that the highest exponent is 1
so we just look for a function that doesn't have an exponent of 1 and that's option C which has an exponent of 4
Answer:
<h2>C = 70π cm</h2><h2>A = 2,450 cm²</h2>
Step-by-step explanation:
The perimeter of the given figure is equal to the circumference of whole circle.
The formula of a circumference of a circle:

d - diameter
We have d = 70 cm. Substitute:

The area of given figure is equal to the area of rectangle 70cm × 35cm.
(look at the picture).
The area of a rectangle:

My back put jalapeño from the asofragus or the diameter of
114