b-7/4=-2/3 what does b equal

Answer:

- The center line is at 16.5 ounces.

- The standard deviation of the sample mean = 0.112 ounce.

- The UCL = 16.836 ounces.

- The LCL = 16.154 ounces.

Step-by-step explanation:

The Central limit theorem allows us to write for a random sample extracted from a normal population distribution with each variable independent of one another that

Mean of sampling distribution (μₓ) is approximately equal to the population mean (μ).

μₓ = μ = 16.5 ounces

And the standard deviation of the sampling distribution is given as

σₓ = (σ/√N)

where σ = population standard deviation = 0.25 ounce

N = Sample size = 5

σₓ = (0.25/√5) = 0.1118033989 = 0.112 ounce

Now using the 3 sigma limit rule that 99.5% of the distribution lies within 3 standard deviations of the mean, the entire distribution lies within

(μₓ ± 3σₓ)

= 16.5 ± (3×0.112)

= 16.5 ± (0.336)

= (16.154, 16.836)

Hope this Helps!!!

Answer:

damien starts with 4 bacteria in a petri dish

f(x) = 5x + 1

table

graph

The graph of the function y = 2x⁴ - 5x³ + x² - 2x + 4 is plotted and attached.

Polynomial is an expression of more than two algebraic terms, especially the sum of several terms that contain different powers of the same variable(s). For example -

y = 4x⁴ + 3x³ + 2x² + 6x + 7

We have the 4 functions as shown in the image attached.

The y - intercept is the point where the graph intercepts the y - axis.

Function [1] -

y = 4 + 2x

y - intercept is 4

Function [2] -

y = 5ˣ + 1

y - intercept is 2.

Function [3] -

the y - intercept is 1.

Function [4] -

the y - intercept is at -1.

Therefore, the greatest y - intercept is of function -

f(x) = 2x + 4

and the least y - intercept is of function shown in graph [4] or function [4].

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Answer:

x = 2

Step-by-step explanation:

the equation of the line can be found using the slope intercept form

y = mx +b

y= -3/2 x + 3

x intercept is found by setting y=0 bc that will give you the x-value at which the line crosses the x -axis so

0 = -3/2x+3 (subtract the 3 on both sides) would cancel out the + 3 and would

-3 = -3/2 x  (divide by -3/2 on both sides to cancel out the -3/2)  

x = 2

Answer:

  see below

Step-by-step explanation:

Subtracting 52 from the y-coordinate of a point moves its location on the graph down 52 units. y=f(x)-52 is shifted down by 52 units from y=f(x).

Answer:

The second graph.

Step-by-step explanation:

0-9: 6 numbers

10-19: 2 numbers

20-29: 1 number

30-39: 3 numbers

40-49: 1 number

50-59: 2 numbers

60-69: 0 numbers

70-79: 5 numbers

80-89: 3 numbers

90-99: 1 number

Answer:

En álgebra, el teorema del factor es un teorema que vincula factores y ceros de un polinomio. Es un caso especial del teorema del resto polinómico.

Step-by-step explanation:

The radioactive compound has a half-life of around 3.09 hours.

The period of time needed for a radioactive substance's initial quantity to decay by half is known as its half-life. The half-life of a drug may be calculated as follows if the rate of decay is proportionate to the amount of the substance existing at time t:

Let t be the half-life of the substance, then after t hours, the amount of the substance present will be,

100 mg × [tex]\dfrac{1}{2}[/tex] = 50 mg.

At time 6 hours, the amount of the substance present is,

100 mg × (1 - 3%) = 97 mg.

Given that the amount of material available determines how quickly something degrades,

The half-life can be calculated as follows:

[tex]t = 6 \times \dfrac{50}{ 97} = 3.09 \ hours[/tex]

Therefore, the half-life of the radioactive substance is approximately 3.09 hours.

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Answer:

49.95+/-0.5543

= ( 49.3957, 50.5043) pounds

the 95% confidence interval (a,b) = ( 49.3957, 50.5043) pounds

And to 2 decimal points;

the 95% confidence interval (a,b) = ( 49.40, 50.50) pounds

Step-by-step explanation:

Confidence interval can be defined as a range of values so defined that there is a specified probability that the value of a parameter lies within it.

The confidence interval of a statistical data can be written as.

x+/-zr/√n

Given that;

Mean x = 49.95 pounds

Standard deviation r = 1.9999 pounds

Number of samples n = 50

Confidence interval = 95%

z value(at 95% confidence) = 1.96

Substituting the values we have;

49.95+/-1.96(1.9999/√50)

49.95+/-1.96(0.282828570338)

49.95+/-0.554343997864

49.95+/-0.5543

= ( 49.3957, 50.5043) pounds

Therefore, the 95% confidence interval (a,b) = ( 49.3957, 50.5043) pounds

Answer:

y=-3

Step-by-step explanation:

-2x+7y=-25

put x=2 in the above equation

-2(2)+7y=-25

-4+7y=-25

adding 4 on both sides

-4+4+7y=-25+4

7y=-21

dividing 7 on both sides

7y/7=-21/7

y=-3

Answer:

A warranty of 6.185 years should be provided.

Step-by-step explanation:

When the distribution is normal, we use the z-score formula.

In a set with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the zscore of a measure X is given by:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

In this question, we have that:

[tex]\mu = 8.2, \sigma = 1.3[/tex]

What warranty should be provided so that the company is replacing at most 6% of their blenders sold?

The warranty should be the 6th percentile, which is X when Z has a pvalue of 0.06. So X when Z = -1.55.

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

[tex]-1.55 = \frac{X - 8.2}{1.3}[/tex]

[tex]X - 8.2 = -1.55*1.3[/tex]

[tex]X = 6.185[/tex]

A warranty of 6.185 years should be provided.

Answer:

Step-by-step explanation:

Ray

Answer:

ray

Step-by-step explanation:

ray is a part of a line that has an endpoint in one side and extends indefinitely on the opposite side. hence, the answer is ray

hope this helps

Complete question is;

In a certain community, 8% of all people above 50 years of age have diabetes. A health service in this community correctly diagnoses 95% of all person with diabetes as having the disease, and incorrectly diagnoses 10% of all person without diabetes as having the disease. Find the probability that a person randomly selected from among all people of age above 50 and diagnosed by the health service as having diabetes actually has the disease.

Answer:

P(has diabetes | positive) = 0.442

Step-by-step explanation:

Probability of having diabetes and being positive is;

P(positive & has diabetes) = P(has diabetes) × P(positive | has diabetes)

We are told 8% or 0.08 have diabetes and there's a correct diagnosis of 95% of all the persons with diabetes having the disease.

Thus;

P(positive & has diabetes) = 0.08 × 0.95 = 0.076

P(negative & has diabetes) = P(has diabetes) × (1 –P(positive | has diabetes)) = 0.08 × (1 - 0.95)

P(negative & has diabetes) = 0.004

P(positive & no diabetes) = P(no diabetes) × P(positive | no diabetes)

We are told that there is an incorrect diagnoses of 10% of all persons without diabetes as having the disease

Thus;

P(positive & no diabetes) = 0.92 × 0.1 = 0.092

P(negative &no diabetes) =P(no diabetes) × (1 –P(positive | no diabetes)) = 0.92 × (1 - 0.1)

P(negative &no diabetes) = 0.828

Probability that a person selected having diabetes actually has the disease is;

P(has diabetes | positive) =P(positive & has diabetes) / P(positive)

P(positive) = 0.08 + P(positive & no diabetes)

P(positive) = 0.08 + 0.092 = 0.172

P(has diabetes | positive) = 0.076/0.172 = 0.442

Using formula:

[tex]P(\text{diabetes diagnosis})\\[/tex]:

[tex]=\text{P(having diabetes and have been diagnosed with it)}\\ + \text{P(not have diabetes and yet be diagnosed with diabetes)}[/tex]

[tex]=0.08 \times 0.95+(1-0.08) \times 0.10 \\\\=0.08 \times 0.95+0.92 \times 0.10 \\\\=0.076+0.092\\\\=0.168[/tex]

[tex]\text{P(have been diagnosed with diabetes)}[/tex]:

[tex]=\frac{\text{P(have diabetic and been diagnosed as having insulin)}}{\text{P(diabetes diagnosis)}}[/tex]

[tex]=\frac{0.08\times 0.95}{0.168} \\\\=\frac{0.076}{0.168} \\\\=0.452\\[/tex]

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Answer:

a prism is a three dimensional shape with the same width all the way through.

Step-by-step explanation:

Step-by-step explanation:

i think this will help.

Answer:

Basically, it is a because the b elevated to the zero results in 1, which multiplies a. Then the initial value is a.

Step-by-step explanation:

The initial value of a function f(x) is f(0), that is, the value of f when x = 0.

Format:

[tex]f(x) = ab^{x}[/tex]

The initial value is f(0). So

[tex]f(x) = ab^{x}[/tex]

[tex]f(0) = ab^{0}[/tex]

Any non-zero value elevated to the zero is 1.

So

[tex]f(0) = ab^{0} = a*1 = a[/tex]

Basically, it is a because the b elevated to the zero results in 1, which multiplies a. Then the initial value is a.

Answer:

SAmple Answer Edge 2020-2021

Step-by-step explanation:

When you substitute 0 for the exponent x, the expression simplifies to a times 1, which is just a. This is because any number to the 0 power equals 1. Since the initial value is the value of the function for an input of 0, the initial value for any function of this form will always be the value of a.

Answer:

We need a sample of at least 1937.

Step-by-step explanation:

In a sample with a number n of people surveyed with a probability of a success of [tex]\pi[/tex], and a confidence level of [tex]1-\alpha[/tex], we have the following confidence interval of proportions.

[tex]\pi \pm z\sqrt{\frac{\pi(1-\pi)}{n}}[/tex]

In which

z is the zscore that has a pvalue of [tex]1 - \frac{\alpha}{2}[/tex].

The margin of error is:

[tex]M = z\sqrt{\frac{\pi(1-\pi)}{n}}[/tex]

For this problem, we have that:

[tex]\pi = 0.72[/tex]

95% confidence level

So [tex]\alpha = 0.05[/tex], z is the value of Z that has a pvalue of [tex]1 - \frac{0.05}{2} = 0.975[/tex], so [tex]Z = 1.96[/tex].

How large a sample should be if you want your estimate to be within 0.02 with 95% confidence.

We need a sample of at least n.

n is found when M = 0.02. So

[tex]M = z\sqrt{\frac{\pi(1-\pi)}{n}}[/tex]

[tex]0.02 = 1.96\sqrt{\frac{0.72*0.28}{n}}[/tex]

[tex]0.02\sqrt{n} = 1.96\sqrt{0.72*0.28}[/tex]

[tex]\sqrt{n} = \frac{1.96\sqrt{0.72*0.28}}{0.02}[/tex]

[tex](\sqrt{n})^{2} = (\frac{1.96\sqrt{0.72*0.28}}{0.02})^{2}[/tex]

[tex]n = 1936.16[/tex]

Rounding up to the nearest number.

We need a sample of at least 1937.

Answer:

True.

95% of all confidence intervals constructed similarly to this one with a sample size of 10 will contain the mean of the population.

Step-by-step explanation:

True.

The confidence level represents the proportion of possible confidence intervals that contain the true mean. In this case, 95% of all confidence intervals of sample size n=10 constructed similarly to this one will contain the population mean.

Answer:

y=5

solution,

X=2

now,

[tex] \\ 5x - y = 5 \\ or \: 5 \times x - y = 5 \\ or \: 5 \times 2 - y = 5 \\ or \: 10 - y = 5 \\ or \: - y = 5 - 10 \\or \: - y = - 5 \\ y = 5[/tex]

hope this helps..

Good luck on your assignment..

Answer:

Hiking: 28%

Canoeing: 16%

Swimming: 24%

Fishing: 32%

Step-by-step explanation:

21 + 12 + 18 + 24 = 75 (there are 75 campers)

21 out of 75 = 28%

12 out of 75 = 16%

18 out of 75 = 24%

24 out of 75 = 32%

Hope this helps!

Please mark Brainliest if correct

Answer:

Option 1.

Step-by-step explanation:

[tex]y=2x+1[/tex]

[tex]x=2y+1[/tex]

[tex]x-1=2y[/tex]

[tex]\frac{x-1}{2} = \frac{2y}{2}[/tex]

[tex]\frac{x-1}{2} = y[/tex]

[tex]\frac{1}{2}x -\frac{1}{2} = y[/tex]

Answer:

  see the attachment

Step-by-step explanation:

You can find the inverse by swapping the variables and solving for y.

  y = f(x) . . . . . original function

  x = f(y) . . . . . variables swapped

  x = 2y +1

  x -1 = 2y . . . subtract 1

  (x-1)/2 = y . . . divide by 2

  y = (1/2)x -1/2 . . . expand

If the inverse function is named h(x), then it is ...

  h(x) = x/2 -1/2

Commission would be total sales x commission rate.

Commission = 3750 x 0.06 = $225

Answer:

Step-by-step explanation:

The formula for determining the confidence interval for the difference of two population means is expressed as

Confidence interval = (x1 - x2) ± z√(s²/n1 + s2²/n2)

Where

x1 = sample mean score of in-state applicants

x2 = sample mean score of out-of-state applicants

s1 = sample standard deviation for in-state applicants

s2 = sample standard deviation for out-of-state applicants

n1 = number of in-state applicants

n2 = number of out-of-state applicants

For a 90% confidence interval, we would determine the z score from the t distribution table because the number of samples are small

Degree of freedom =

(n1 - 1) + (n2 - 1) = (8 - 1) + (17 - 1) = 23

z = 1.714

x1 - x2 = 1144 - 1200 = - 56

Margin of error = z√(s1²/n1 + s2²/n2) = 1.714√(25²/8 + 26²/17) = 18.61

Confidence interval = - 56 ± 18.61

Answer:

Let's solve your equation step-by-step.

[tex]x^7+64x^4=0[/tex]

Step 1: Factor left side of equation.

[tex]x^4(x+4)(x^2-4x+16)=0[/tex]

Step 2: Set factors equal to 0.

[tex]x^4=0[/tex]  or  [tex]x+4=0[/tex]  or  [tex]x^2-4x+16=0[/tex] 

[tex]x^4=0[/tex]  or  [tex]x=0[/tex]  

Answer:

I hope this help you :)

Answer:

At least 202.44 mm in the top 15%.

Step-by-step explanation:

When the distribution is normal, we use the z-score formula.

In a set with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the zscore of a measure X is given by:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

In this question, we have that:

[tex]\mu = 134, \sigma = 66[/tex]

How many yearly mm of rainfall would there be in the top 15%?

At least X mm.

X is the 100-15 = 85th percentile, which is X when Z has a pvalue of 0.85. So X when Z = 1.037.

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

[tex]1.037 = \frac{X - 134}{66}[/tex]

[tex]X - 134 = 66*1.037[/tex]

[tex]X = 202.44[/tex]

At least 202.44 mm in the top 15%.

Answer:

[tex]25[/tex]

Step-by-step explanation:

[tex](4 + 6 \times 3) + 3[/tex]

[tex]=(4 + 18) + 3[/tex]

[tex]=(22) + 3[/tex]

[tex]=22+3[/tex]

[tex]=25[/tex]

Answer:25

Step-by-step explanation:

Pemdas

(4+6*3)+3

(Parentheses and Multiplication first)

4+18

22+3

Then addition

22+3=25

Using the Central Limit Theorem, it is found that the measures are given by:

a) 2,500,000.

b) 88,388.35.

c) 2,500,000.

By the Central Limit Theorem, the sampling distribution of sample means of size n for a population of mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex] has the same mean as the population, but with standard deviation [tex]s = \frac{\sigma}{\sqrt{n}}[/tex]

Hence, we have that for options a and c, the mean is of 2,500,000 users, while for option b, the standard deviation is given by:

[tex]s = \frac{\sigma}{\sqrt{n}} = \frac{625000}{\sqrt{50}} = 88,388.35.[/tex]

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Answer:

a) 0.6426 = 64.26% probability that the sample mean will be within +/- 5 of the population mean.

b) 0.9544 = 95.44% probability that the sample mean will be within +/- 10 of the population mean.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

When the distribution is normal, we use the z-score formula.

In a set with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the zscore of a measure X is given by:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean [tex]\mu[/tex] and standard deviation [tex]s = \frac{\sigma}{\sqrt{n}}[/tex].

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

In this question, we have that:

[tex]\mu = 200, \sigma = 50, n = 100, s = \frac{50}{\sqrt{100}} = 5[/tex]

a. What is the probability that the sample mean will be within +/- 5 of the population mean (to 4 decimals)?

This is the pvalue of Z when X = 200 + 5 = 205 subtracted by the pvalue of Z when X = 200 - 5 = 195.

Due to the Central Limit Theorem, Z is:

[tex]Z = \frac{X - \mu}{s}[/tex]

X = 205

[tex]Z = \frac{X - \mu}{s}[/tex]

[tex]Z = \frac{205 - 200}{5}[/tex]

[tex]Z = 1[/tex]

[tex]Z = 1[/tex] has a pvalue of 0.8413.

X = 195

[tex]Z = \frac{X - \mu}{s}[/tex]

[tex]Z = \frac{195 - 200}{5}[/tex]

[tex]Z = -1[/tex]

[tex]Z = -1[/tex] has a pvalue of 0.1587.

0.8413 - 0.1587 = 0.6426

0.6426 = 64.26% probability that the sample mean will be within +/- 5 of the population mean.

b. What is the probability that the sample mean will be within +/- 10 of the population mean (to 4 decimals)?

This is the pvalue of Z when X = 210 subtracted by the pvalue of Z when X = 190.

X = 210

[tex]Z = \frac{X - \mu}{s}[/tex]

[tex]Z = \frac{210 - 200}{5}[/tex]

[tex]Z = 2[/tex]

[tex]Z = 2[/tex] has a pvalue of 0.9772.

X = 195

[tex]Z = \frac{X - \mu}{s}[/tex]

[tex]Z = \frac{190 - 200}{5}[/tex]

[tex]Z = -2[/tex]

[tex]Z = -2[/tex] has a pvalue of 0.0228.

0.9772 - 0.0228 = 0.9544

0.9544 = 95.44% probability that the sample mean will be within +/- 10 of the population mean.

(a): The required probability is [tex]P(195 < \bar{x} < 205)=0.6826[/tex]

(b): The required probability is [tex]P(190 < \bar{x} < 200)=0.9544[/tex]

A numerical measurement that describes a value's relationship to the mean of a group of values.

Given that,

mean=200

Standard deviation=50

[tex]n=100[/tex]

[tex]\mu_{\bar{x}}=200[/tex]

[tex]\sigma{\bar{x}} =\frac{\sigma}{\sqrt{n} } \\=\frac{50}{\sqrt{100} }\\ =5[/tex]

Part(a):

within [tex]5=200\pm 5=195,205[/tex]

[tex]P(195 < \bar{x} < 205)=P(-1 < z < 1)\\=P(z < 1)-P(z < -1)\\=0.8413-0.1587\\=0.6826[/tex]

Part(b):

within [tex]10=200\pm 10=190,200[/tex]

[tex]P(190 < \bar{x} < 200)=P(-1 .98 < z < 1.98)\\=P(z < 2)-P(z < -2)\\=0.9772-0.0228\\=0.9544[/tex]

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Answer:

A

Step-by-step explanation:

The area of a kite is half of the product of the length of the diagonals, or in this case 16*12/2=96 square feet. Hope this helps!

Answer:

a. 96 ft^2

Step-by-step explanation:

You can cut the kite into 2 equal triangle halves vertically.

Then you can use the triangle area formula and multiply it by 2 since there are 2 triangles.

[tex]\frac{1}{2} *12*8*2=\\6*8*2=\\48*2=\\96ft^2[/tex]

The kite's area is a. 96 ft^2.

Answer: x=45°

Step-by-step explanation:

Angles opposite from each other are equal. The angle 160 degrees in red on the bottom encompasses two angles: BEG and CEG. Angle BEG is on the opposite side as FEA which means it is equal to x.

Since angle FED on the other side is 115, you subtract 115 from 160 to get 45 degrees.

Answer: x=45°

The angle BEG, which is opposite to the angle FEA, is determined to be 45 degrees.

According to the information provided, in a figure with an angle of 160 degrees (red angle on the bottom), there are two angles labeled as BEG and CEG. It is stated that the angle BEG is opposite to the angle FEA, making them equal, so we can represent this angle as x.

Additionally, it is mentioned that the angle FED on the other side measures 115 degrees.

To find the value of x, we subtract 115 degrees from the angle of 160 degrees.
=160-115
= 45

Thus, the solution is x = 45°.

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Answer:

The probability of healthcare expenses in the population being greater than $4,000 is 0.02275.

Step-by-step explanation:

We are given that yearly healthcare expenses for a family of four are normally distributed with a mean expense equal to $3,000 and a standard deviation equal to $500.

Let X = yearly healthcare expenses of a family

The z-score probability distribution for the normal distribution is given by;

                            Z  =  [tex]\frac{ X-\mu}{\sigma} }[/tex]  ~ N(0,1)

where, [tex]\mu[/tex] = population mean expense = $3,000

            [tex]\sigma[/tex] = standard deviation = $500

Now, the probability of healthcare expenses in the population being greater than $4,000 is given by = P(X > $4,000)

     P(X > $4,000) = P( [tex]\frac{ X-\mu}{\sigma} }[/tex] > [tex]\frac{4,000-3,000}{{500}{ } }[/tex] ) = P(Z > 2) = 1 - P(Z [tex]\leq[/tex] 2)

                                                                  = 1 - 0.97725 = 0.02275

The above probability is calculated by looking at the value of x = 2 in the z table which has an area of 0.97725.