Which statement about perfect cubes is true?

Answer:

I'm not completely sure what you mean by a, "single fraction," but I'm pretty sure the answer you are looking for is [tex]\frac{5-4}{a-b}[/tex]

Step-by-step explanation:

Answer:

24.5

Step-by-step explanation:

24 = 24

1/2 -->

convert to a decimal => 1 divided by 2

0.5

24+0.5 = 24.5

Hope this helps!

Answer:

Is possible to make a Type I error, where we reject a true null hypothesis.

Step-by-step explanation:

We have a hypothesis test of a proportion. The claim is that the proportion of paid leave has significantly decrease from 2011 to january 2012. The P-value for this test is 0.0271 and the nunll hypothesis is rejected.

As the conclusion is to reject the null hypothesis, the only error that we may have comitted is rejecting a true null hypothesis.

The null hypothesis would have stated that there is no significant decrease in the proportion of paid leave.

This is a Type I error, where we reject a true null hypothesis.

Answer : The value of x is 4.1 cm.

Step-by-step explanation :

As we know that the perpendicular dropped from the center divides the chord into two equal parts.

That means,

AB = CB = [tex]\frac{15.6cm}{2}=7.8cm[/tex]

Now we have o calculate the value of x by using Pythagoras theorem.

Using Pythagoras theorem in ΔOBA :

[tex](Hypotenuse)^2=(Perpendicular)^2+(Base)^2[/tex]

[tex](OA)^2=(OB)^2+(BA)^2[/tex]

Now put all the values in the above expression, we get the value of side OB.

[tex](8.8)^2=(x)^2+(7.8)^2[/tex]

[tex]x=\sqrt{(8.8)^2-(7.8)^2}[/tex]

[tex]x=\sqrt{77.44-60.84}[/tex]

[tex]x=\sqrt{16.6}[/tex]

[tex]x=4.074\approx 4.1[/tex]

Therefore, the value of x is 4.1 cm.

Answer:

[tex] 9.9676 - 2.326*0.5904 =8.594[/tex]

[tex] 9.9676 + 2.326*0.5904 =11.341[/tex]

Step-by-step explanation:

Notation

[tex]\bar X[/tex] represent the sample mean

[tex]\mu[/tex] population mean (variable of interest)

s represent the sample standard deviation

n represent the sample size  

Solution to the problem

The confidence interval for the mean is given by the following formula:

[tex]\bar X \pm t_{\alpha/2}\frac{s}{\sqrt{n}}[/tex]   (1)

For this case the 9% confidence interval is given by:

[tex] 8.8104 \leq \mu \leq 11.1248[/tex]

We can calculate the mean with the following:

[tex]\bar X = \frac{8.8104 +11.1248}{2}= 9.9676[/tex]

And we can find the margin of error with:

[tex] ME= \frac{11.1248- 8.8104}{2}= 1.1572[/tex]

The margin of error for this case is given by:

[tex] ME = t_{\alpha/2}\frac{s}{\sqrt{n}} = t_{\alpha/2} SE[/tex]

And we can solve for the standard error:

[tex] SE = \frac{ME}{t_{\alpha/2}}[/tex]

The critical value for 95% confidence using the normal standard distribution is approximately 1.96 and replacing we got:

[tex] SE = \frac{1.1572}{1.96}= 0.5904[/tex]

Now for the 98% confidence interval the significance is [tex]\alpha=1-0.98= 0.02[/tex] and [tex]\alpha/2 = 0.01[/tex] the critical value would be 2.326 and then the confidence interval would be:

[tex] 9.9676 - 2.326*0.5904 =8.594[/tex]

[tex] 9.9676 + 2.326*0.5904 =11.341[/tex]

Answer:

P(B1) = (11/15)

P(B2) = (4/15)

P(A) = (11/15)

P(B1|A) = (5/7)

P(B2|A) = (2/7)

Step-by-step explanation:

There are 11 red chips and 4 blue chips in a box. Two chips are selected one after the other at random and without replacement from the box.

B1 is the event that the chip removed from the box at the first step of the experiment is red.

B2 is the event that the chip removed from the box at the first step of the experiment is blue. A is the event that the chip selected from the box at the second step of the experiment is red.

Note that the probability of an event is the number of elements in that event divided by the Total number of elements in the sample space.

P(E) = n(E) ÷ n(S)

P(B1) = probability that the first chip selected is a red chip = (11/15)

P(B2) = probability that the first chip selected is a blue chip = (4/15)

P(A) = probability that the second chip selected is a red chip

P(A) = P(B1 n A) + P(B2 n A) (Since events B1 and B2 are mutually exclusive)

P(B1 n A) = (11/15) × (10/14) = (11/21)

P(B2 n A) = (4/15) × (11/14) = (22/105)

P(A) = (11/21) + (22/105) = (77/105) = (11/15)

P(B1|A) = probability that the first chip selected is a red chip given that the second chip selected is a red chip

The conditional probability, P(X|Y) is given mathematically as

P(X|Y) = P(X n Y) ÷ P(Y)

So, P(B1|A) = P(B1 n A) ÷ P(A)

P(B1 n A) = (11/15) × (10/14) = (11/21)

P(A) = (11/15)

P(B1|A) = (11/21) ÷ (11/15) = (15/21) = (5/7)

P(B2|A) = probability that the first chip selected is a blue chip given that the second chip selected is a red chip

P(B2|A) = P(B2 n A) ÷ P(A)

P(B2 n A) = (4/15) × (11/14) = (22/105)

P(A) = (11/15)

P(B2|A) = (22/105) ÷ (11/15) = (2/7)

Hope this Helps!!!

Answer:

3/10

Step-by-step explanation:

Answer:

P(7 or 11) = 0.2222

Step-by-step explanation:

First let's find the cases where we get a sum of 7 and a sum of 11:

The cases where we get a sum of 7 are:

(1,6), (2,5), (3,4), (4,3), (5,2), (6,1)

And the cases where we get a sum of 11 are:

(5,6), (6,5)

So we have a total of 8 cases among the 36 total possible outcomes.

So the probability of the sum of the two dice being 7 or 11 is:

P(7 or 11) = 8 / 36 = 0.2222

Answer:

$38,645.7208

Step-by-step explanation:

Given that

Principal = $70,000

Time = 20 years

Rate = 2.2%

The calculation of the amount of saving is shown below:-

[tex]=P(1+r)^t[/tex]

A = Future amount

P = Principal amount  

[tex]r = \frac{APR}{12}[/tex]  

[tex]r = \frac{0.022}{12}[/tex]

0.001833333

t = 20 years which is equals to 240 months

[tex]A=\$70,000\times (1+0.001833333)^{240}[/tex]

[tex]A=\$70,000\times 1.552081726[/tex]

= $108,645.7208

And, the loan amount for 20 years is $70,000

So,

He would save by paying off 9 years early is

= $108,645.7208  - $70,000

= $38,645.7208

Its $3644.67  since everyone couldn't find it solved it myself ;)

Answer:

Option B

Step-by-step explanation:

Before a researcher specifies the relationship among variables he must have an inventory of propositions/constructs which are mostly stated in a declarative form. These are then tested by examining the relationships between measurable variables of this constructs/propositions.

Answer:

For a sample size of n = 609.

Step-by-step explanation:

Central limit theorem for proportions:

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean [tex]\mu = p[/tex] and standard deviation [tex]s = \sqrt{\frac{p(1-p)}{n}}[/tex]

In this question:

We have that p = 0.58.

We have to find n for which s = 0.02. So

[tex]s = \sqrt{\frac{p(1-p)}{n}}[/tex]

[tex]0.02 = \sqrt{\frac{0.58*0.42}{n}}[/tex]

[tex]0.02\sqrt{n} = \sqrt{0.58*0.42}[/tex]

[tex]\sqrt{n} = \frac{\sqrt{0.58*0.42}}{0.02}[/tex]

[tex](\sqrt{n})^{2} = (\frac{\sqrt{0.58*0.42}}{0.02})^{2}[/tex]

[tex]n = 609[/tex]

For a sample size of n = 609.

Answer:

I hope this help

Step-by-step explanation:

Answer:

the answer is 3

Step-by-step explanation:

i took the test

Answer:

Step-by-step explanation:

The question is incomplete. The complete question is:

The mean annual tuition and fees for a sample of 15 private colleges was $35,500 with a standard deviation of $6500. A dotplot shows that it is reasonable to assume that the population is approximately normal. You wish to test whether the mean tuition and fees for private colleges is different from $32,500. State the null and alternate hypotheses. A) H0: 4 = 32,500, H:4=35,500 C) H: 4 = 35,500, H7:35,500 B) H: 4 = 32,500, H : 4 # 32,500 D) H0:41 # 32,500, H : 4 = 32,500

Solution

We would set up the hypothesis test. This is a test of a single population mean since we are dealing with mean

For the null hypothesis,

H0: µ = 32500

For the alternative hypothesis,

Ha: µ ≠ 32500

This is a two tailed test.

Since the number of samples is small and the population standard deviation is not given, the distribution is a student's t.

Since n = 15,

Degrees of freedom, df = n - 1 = 15 - 1 = 14

t = (x - µ)/(s/√n)

Where

x = sample mean = 35500

µ = population mean = 32500

s = samples standard deviation = 6500

t = (35500 - 32500)/(6500/√15) = 1.79

We would determine the p value using the t test calculator. It becomes

p = 0.095

Assuming alpha = 0.05

Since alpha, 0.05 < than the p value, 0.095, then we would fail to reject the null hypothesis.

Answer:

Step-by-step explanation:

Answer:

B

Step-by-step explanation:

Answer:

Volume of the cone is 1883.7 cm³

Step-by-step explanation:

The circumference of the full circle with radius 18 cm :

360 := 2*π*18 = 36π cm

125 := 125/360 * 36π

The new circumference is maller:

36π - 125/360 * 36π

36π * 0.652(7)

Calculate the new r based on the new circomference:

2*π * r = 36π * 0.652(7)

r = 36π/2π * 0.652(7)

r = 18 * 0.652(7)

r = 11.75 cm

Based on this radius you can calculate the area of the base of the cone.

area base = π*(11.75)²

The Volume V of this cone = 1/3 π r² * h

You can calculate the height h by using Pythagoras theorum.

The sector is the hypothenusa= 18 cm

The h is the height, which is the "unknown"

The r is the new radius = 11.75 cm

s² = r² + h²

h² = s² - r²

h = √(s² - r²)

h = √(18² - 11.75²)

h = 13.6358901432946 cm

h = 13.636 cm

V cone

V = 1/3 π 11.75² * h

V = 1/3 π 11.75² * √(18² - 11.75²)

V = 1/3 π 11.75² * 13.636

V = 1883.7 cm³

Answer:

india

Step-by-step explanation:

Answer:  b) the tiles are not similar because both SP:SR is 5:4 and MJ:ML is 5:2

Step-by-step explanation:

We are given that the tiles are rectangular which implies that they both have a 90° angle.

In order to prove similarity, We need to show that the lengths and widths are proportional.

P Q R S

J  K L M

a) PQ : QR         JK : LM

  w=4  L=5        w=2 w=2

                                  ↓

                                 We need Length (not width)

b) SP : SR         MJ : ML

  L=5  w=4        L=5 w=2

      5 : 4               5 : 2

When comparing length to width they do not have the same ratio so the rectangles are not similar.

c) PQ : QR         JK : KL

  w=4  L=5        w=2 L=5

      4 : 5               2 : 5

When comparing width to length they do not have the same ratio so the rectangles are not similar.

d) SR : ML         PQ : JK

  w=4  w=2        w=4 w=2

           ↓                     ↓

  We need Length (not width)

Answer:

root 61

Step-by-step explanation:

You can use the distance formula or draw a triangle with sides 5 and 6

Answer:

y = 2/3x + 4

Step-by-step explanation:

Step 1: Find slope

m = (4-0)/(0+6)

m = 2/3

Step 2: Write in y-int (0, 4)

y = 2/3x + 4

Answer:

There is not enough evidence to support the claim that the amount of vitamin C in a tablet sample is different from 500 mg.

P-value = 0.166.

Step-by-step explanation:

We start by calculating the mean and standard deviation of the sample:

[tex]M=\dfrac{1}{n}\sum_{i=1}^n\,x_i\\\\\\M=\dfrac{1}{5}(490+502+505+495+492)\\\\\\M=\dfrac{2484}{5}\\\\\\M=496.8\\\\\\s=\sqrt{\dfrac{1}{n-1}\sum_{i=1}^n\,(x_i-M)^2}\\\\\\s=\sqrt{\dfrac{1}{4}((490-496.8)^2+(502-496.8)^2+(505-496.8)^2+(495-496.8)^2+(492-496.8)^2)}\\\\\\s=\sqrt{\dfrac{166.8}{4}}\\\\\\s=\sqrt{41.7}=6.5\\\\\\[/tex]

Then, we can perform the hypothesis t-test for the mean.

The claim is that the amount of vitamin C in a tablet sample is different from 500 mg.

Then, the null and alternative hypothesis are:

[tex]H_0: \mu=500\\\\H_a:\mu< 500[/tex]

The significance level is 0.05.

The sample has a size n=5.

The sample mean is M=496.8.

As the standard deviation of the population is not known, we estimate it with the sample standard deviation, that has a value of s=6.5.

The estimated standard error of the mean is computed using the formula:

[tex]s_M=\dfrac{s}{\sqrt{n}}=\dfrac{6.5}{\sqrt{5}}=2.907[/tex]

Then, we can calculate the t-statistic as:

[tex]t=\dfrac{M-\mu}{s/\sqrt{n}}=\dfrac{496.8-500}{2.907}=\dfrac{-3.2}{2.907}=-1.1[/tex]

The degrees of freedom for this sample size are:

[tex]df=n-1=5-1=4[/tex]

This test is a left-tailed test, with 4 degrees of freedom and t=-1.1, so the P-value for this test is calculated as (using a t-table):

[tex]\text{P-value}=P(t<-1.1)=0.166[/tex]

As the P-value (0.166) is bigger than the significance level (0.05), the effect is not significant.

The null hypothesis failed to be rejected.

There is not enough evidence to support the claim that the amount of vitamin C in a tablet sample is different from 500 mg.

Answer:

x = 8

Step-by-step explanation:

Step 1: Write out the expression

x + 2x = 24

Step 2: Combine like terms

3x = 24

Step 3: Isolate x

x = 8

And we have our final answer!

Answer:

X=8

Step-by-step explanation:

Answer:

-1/4 is the slope and the y intercept is -4

Step-by-step explanation:

Solve for y

x +4y = -16

Subtract x

4y = -x-16

Divide by 4

4y/4 = -x/4 -16/4

y = -1/4 x -4

This is in slope intercept form

y = mx+b where m is the slope and b is the y intercept

-1/4 is the slope and the y intercept is -4

Answer:

91 employees

Step-by-step explanation:

To find the number of employees absent fewer than six days...add the frequency of those absent for 0 to 3 days and that of 3 to 6 days

The frequency of 0 to 3 days = 60

The frequency of 3 to 6 days = 31

Thus, the numbers of employees absent fewer than 6 days is 60+31 = 91

Answer:

[tex]\mu_1 \neq \mu_2 \neq \mu_3[/tex]

Where [tex]\mu_1[/tex] is the average effect of strength training

[tex]\mu_2[/tex] is the average effect of aerobic training

[tex]\mu_3[/tex] is the average effect of yoga

Step-by-step explanation:

The aim of this study is to confirm whether the strength training, aerobic training, and yoga have equal effect on the decreasing rates of injury and absenteeism or not. The null hypothesis suggests that these three training have equal effect on the decreasing rates of injury and absenteeism because according to the null hypothesis, there is no statistical difference between observed variables.

The alternative hypothesis on the other hand suggests a statistical difference between the observed variables. In this case, the alternative hypothesis suggests that the observed variables have different effects on the decreasing rates of injury and absenteeism.

My alternative hypothesis as the director of the employee wellness and productivity program is [tex]\mu_1 \neq \mu_2 \neq \mu_3[/tex]

Where [tex]\mu_1[/tex] is the average effect of strength training

[tex]\mu_2[/tex] is the average effect of aerobic training

[tex]\mu_3[/tex] is the average effect of yoga

The alternative hypothesis is, [tex]\mu_1 \neq \mu_2 \neq \mu_ 3[/tex].

Where, [tex]\mu_1[/tex] is the average effect of strength training,

[tex]\mu_2[/tex] is the average effect of aerobic training.

[tex]\mu_3[/tex] is the average effect of yoga.

Given that,

As director of the employee wellness and productivity program in your company,

you are interested in comparing the effects of strength training, aerobic training, and yoga on decreasing rates of injury and absenteeism.

The company has 9 divisions with roughly the same number of employees, and you randomly assign 3 divisions to participate in strength training, 3 to aerobic training, and 3 to yoga.

We have to determine,

Your alternative hypothesis is.

According to the question,

The effects of strength training, aerobic training, and yoga on decreasing rates of injury and absenteeism.

The aim of this study is to confirm whether strength training, aerobic training, and yoga have equal effects on decreasing rates of injury and absenteeism or not.

The null hypothesis suggests that these three pieces of training have an equal effect on the decreasing rates of injury and absenteeism because according to the null hypothesis,

There is no statistical difference between observed variables.

The alternative hypothesis on the other hand suggests a statistical difference between the observed variables.

In this case, the alternative hypothesis suggests that the observed variables have different effects on the decreasing rates of injury and absenteeism.

The company has 9 divisions with roughly the same number of employees, and you randomly assign 3 divisions to participate in strength training, 3 to aerobic training, and 3 to yoga.

Therefore, The alternative hypothesis as the director of the employee wellness and productivity program is,

Where [tex]\mu_1[/tex] is the average effect of strength training,

[tex]\mu_2[/tex] is the average effect of aerobic training.

[tex]\mu_3[/tex] is the average effect of yoga.

To know more about the Hypothesis click the link given below.

https://brainly.com/question/23056080

Answer:

The value of the sample mean resonance frequency is 112Hz

Step-by-step explanation:

A confidence interval has two bounds, a lower bound and an upper bound.

A confidence interval is symmetric, which means that the point estimate used is the mid point between these two bounds, that is, the mean of the two bounds.

In this problem, we have that:

Lower bound: 111.6

Upper bound: 112.4

Sample mean: (111.6 + 112.4)/2 = 112Hz

The value of the sample mean resonance frequency is 112Hz

The value of the sample mean resonance frequency is 112 Hz.

The value of the sample mean resonance frequency is equivalent to the average of the upper limit and the lower limit.

The sample mean resonance frequency = (lower limit + upper limit) / 2

(111.6 +112.4) / 2

= 224 / 2

= 112 Hz

To learn more about confidence interval, please check: https://brainly.com/question/15905477

Answer:

For this case they want to proof if the proportion of readers own a Rolls royce is less than 0.29 and that wuld be the alternative hypothesis. The complement would represent the null hypothesis. Then the system of hypothesis for this case are:

Null hypothesis: [tex] p \geq 0.29[/tex]

Alternative hypothesis: [tex]p< 0.29[/tex]

Step-by-step explanation:

For this case they want to proof if the proportion of readers own a Rolls royce is less than 0.29 and that wuld be the alternative hypothesis. The complement would represent the null hypothesis. Then the system of hypothesis for this case are:

Null hypothesis: [tex] p \geq 0.29[/tex]

Alternative hypothesis: [tex]p< 0.29[/tex]

Answer:

(C)Out of 5,000 randomly chosen children, 250 children carry the virus.

Step-by-step explanation:

[tex]\text{Option A}: \dfrac{210}{5000}=0.042=4.2\% \\\text{Option B}: \dfrac{3}{60}=0.05=5\% \\\text{Option C}: \dfrac{250}{5000}=0.05=5\% \\\text{Option D}: \dfrac{1}{20}=0.05=5\%[/tex]

The higher the research sample, the more credible the results. In options A and C, the research sample was 5000. However, since the relative frequency of children carrying the virus is 5% in both, we take the result with a higher number of positives.

Option C is the correct option.

Answer:

Step-by-step explanation:

given a point [tex](x_0,y_0)[/tex] the equation of a line with slope m that passes through the  given point is

[tex]y-y_0 = m(x-x_0)[/tex] or equivalently

[tex] y = mx+(y_0-mx_0)[/tex].

Recall that a line of the form [tex]y=mx+b [/tex], the y intercept is b and the x intercept is [tex]\frac{-b}{m}[/tex].

So, in our case, the y intercept is [tex](y_0-mx_0)[/tex] and the x  intercept is [tex]\frac{mx_0-y_0}{m}[/tex].

In our case, we know that the line is tangent to the graph of 1/x. So consider a point over the graph [tex](x_0,\frac{1}{x_0})[/tex]. Which means that [tex]y_0=\frac{1}{x_0}[/tex]

The slope of the tangent line is given by the derivative of the function evaluated at [tex]x_0[/tex]. Using the properties of derivatives, we get

[tex]y' = \frac{-1}{x^2}[/tex]. So evaluated at [tex]x_0[/tex] we get [tex] m = \frac{-1}{x_0^2}[/tex]

Replacing the values in our previous findings we get that the y intercept is

[tex](y_0-mx_0) = (\frac{1}{x_0}-(\frac{-1}{x_0^2}x_0)) = \frac{2}{x_0}[/tex]

The x intercept is

[tex] \frac{mx_0-y_0}{m} = \frac{\frac{-1}{x_0^2}x_0-\frac{1}{x_0}}{\frac{-1}{x_0^2}} = 2x_0[/tex]

The triangle in consideration has height [tex]\frac{2}{x_0}[/tex] and base [tex]2x_0[/tex]. So the area is

[tex] \frac{1}{2}\frac{2}{x_0}\cdot 2x_0=2[/tex]

So regardless of the point we take on the graph, the area of the triangle is always 2.