Step-by-step explanation:
Part A:
can be written as the square of u³, or
. Similarly,
. Hence, we can write this as a difference of two squares by writing it as

Part B:
<h3>Difference of Two Squares</h3>
<u>We can first factor a difference of two squares a² - b² into </u><u>(a+b)(a-b)</u>. Here, <em>a</em> would be u³ and <em>b</em> would be v³.

<h3>Sum and Difference of Two Cubes</h3>
We can factor this further by the use of two special formulas to factor a sum of two cubes and a difference of two cubes. These formulas are as follows:

Since u³ + v³ is a sum of two cubes, let's rewrite it.

Since u³ - v³ is a difference of two cubes, we can rewrite it as well.

Now, let's multiply them together again to get the final factored form.

Part C:
If we want to factor
completely, we can just see that x to the sixth power is just
and 1 to the sixth power is just 1. Hence, x can substitute for <em>u </em>and 1 can substitute for v.

We can repeat this for
, as 64 is just 2 to the sixth power.

Answer:
Part (A): The correct option is true.
Part (B): The null and alternative hypothesis should be:

Step-by-step explanation:
Consider the provided information.
Part (A)
A random sample of 100 students from a large university.
Increasing the sample size decreases the confidence intervals, as it increases the standard error.
If the researcher increase the sample size to 150 which is greater than 100 that will decrease the confidence intervals or the researcher could produce a narrower confidence interval.
Hence, the correct option is true.
Part (B)
The researcher wants to identify that whether there is any significant difference between the measurement of the blood pressure.
Therefore, the null and alternative hypothesis should be:

X is minus 2
y is equal to 1
Answer:
Confidence interval variance [21.297 ; 64.493]
Confidence interval standard deviation;
4.615, 8.031
Step-by-step explanation:
Given :
Variance, s² = 34.34
Standard deviation, s = 5.86
Sample size, n = 27
Degree of freedom, df = 27 - 1 = 26
Using the relation for the confidence interval :
[s²(n - 1) / X²α/2, n-1] ; [s²(n - 1) / X²1-α/2, n-1]
From the chi distribition table :
X²α/2, n-1 = 41.923 ; X²1-α/2, n-1 = 13.844
Hence,
[34.34*26 / 41.923] ; [34.34*26 / 13.844]
[21.297 ; 64.493]
The 95% confidence interval for the population variance is :
21.297 < σ² < 64.493
Standard deviation is the square root of variance, hence,
The 95% confidence interval for the population standard deviation is :
4.615 < σ < 8.031