Answer:
Error Bound = 0.04
Step-by-step explanation:
Whenever we want to estimate parameter from a subset (or sample) of the population, we need to considerate that your estimation won't be a 100% precise, in other words, the process will have a random component that prevents us from always making the exact decision.
With that in mind, the objective of a confidence interval is to give us a better insight of where we expect to find the "true" value of the parameter with a certain degree of certainty.
The estivamative of the true difference between proportions was -0.19 and the confidence interval was [-0.23 ; -0.15].
The question also defines the error bound, as the right endpoint of the confidence interval minus the sample mean difference, so it's pretty straight foward:
Error Bound = 
The interpretation of this would be that we expect that the estimative for the difference of proportions would deviate from the "true" difference about 
or 4%.
Answer:
option D
D. x = 5, y = 2
Step-by-step explanation:
Given in the question two equation,
Equation 1
5.3x + y = 28.5
Equation 2
4.2x + 3.1y = 27.2
rearrange equation 1 in terms of y
y = 28.5 - 5.3x
Substitute the value of y in equation 2
<h3>4.2x + 3.1(28.5 - 5.3x) = 27.2</h3>
4.2x + 88.35 - 16.43x = 27.2
4.2x - 16.43x = 27.2 - 88.35
-12.23x = -61.15
x = 61.15/12.23
x = 5
put value of x in any of the equation
<h3>5.3(5) + y = 28.5</h3>
y = 28.5 - 26.5
y = 2
Answer:
Step-by-step explanation:
<em>Key Differences Between Covariance and Correlation
</em>
<em>The following points are noteworthy so far as the difference between covariance and correlation is concerned:
</em>
<em>
</em>
<em>1. A measure used to indicate the extent to which two random variables change in tandem is known as covariance. A measure used to represent how strongly two random variables are related known as correlation.
</em>
<em>2. Covariance is nothing but a measure of correlation. On the contrary, correlation refers to the scaled form of covariance.
</em>
<em>3. The value of correlation takes place between -1 and +1. Conversely, the value of covariance lies between -∞ and +∞.
</em>
<em>4. Covariance is affected by the change in scale, i.e. if all the value of one variable is multiplied by a constant and all the value of another variable are multiplied, by a similar or different constant, then the covariance is changed. As against this, correlation is not influenced by the change in scale.
</em>
<em>5. Correlation is dimensionless, i.e. it is a unit-free measure of the relationship between variables. Unlike covariance, where the value is obtained by the product of the units of the two variables.
</em>
You can find more here: http://keydifferences.com/difference-between-covariance-and-correlation.html#ixzz4qg5YbiGj
The <em>simple annual interest</em> rate for the $ 525 loan is equal to 46.35 %.
<h3>What is the interest rate behind a pay back?</h3>
In this situation we assume that the loan does not accumulate interests continuously in time. Hence, the <em>interest</em> rate for paying the loan back 75 days later is:
575 = 525 · (1 + r/100)
50 = 525 · r /100
5000 = 525 · r
r = 9.524
The loan has an <em>interest</em> rate of 9.524 % for 75 days. <em>Simple annual interest</em> rate is determine by rule of three:
r' = 9.524 × 365/75
r' = 46.350
The <em>simple annual interest</em> rate for the $ 525 loan is equal to 46.35 %.
To learn more on interests: brainly.com/question/26457073
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Answer:
ITS 8 x 4 = 32 OK REEE
Step-by-step explanation:
