A car which was advertised for sale for 95000, was ultimately sold for 83600. Find the percent reduction in the price?
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Answer:

15400 books

Step-by-step explanation:

in the first year he sold =6859 books

in the second year he sold =8541 books

therefore, to find the book he sold altogether

6859+8541

= 15400 books altogether

Answer:

15400 books altogether.

Explanation:

Books sold in 1st year: 6859

Books sold in 2nd year: 8541

Total books sold:

                            6859 + 8541 = 15400.

Answer:

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Step-by-step explanation:

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Answer:

0.91824 = 91.824% probability that more than 3 students will have their automobiles stolen during the current semester.

Step-by-step explanation:

We have only the mean, which means that the Poisson distribution is used to solve this question.

In a Poisson distribution, the probability that X represents the number of successes of a random variable is given by the following formula:

[tex]P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}[/tex]

In which

x is the number of sucesses

e = 2.71828 is the Euler number

[tex]\mu[/tex] is the mean in the given interval.

Suppose that on the average, 7 students enrolled in a small liberal arts college have their automobiles stolen during the semester.

This means that [tex]\mu = 7[/tex]

What is the probability that more than 3 students will have their automobiles stolen during the current semester?

This is:

[tex]P(X > 3) = 1 - P(X \leq 3)[/tex]

In which

[tex]P(X \leq 3) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3)[/tex]

So

[tex]P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}[/tex]

[tex]P(X = 0) = \frac{e^{-7}*7^{0}}{(0)!} = 0.00091[/tex]

[tex]P(X = 1) = \frac{e^{-7}*7^{1}}{(1)!} = 0.00638[/tex]

[tex]P(X = 2) = \frac{e^{-7}*7^{2}}{(2)!} = 0.02234[/tex]

[tex]P(X = 3) = \frac{e^{-7}*7^{3}}{(3)!} = 0.05213[/tex]

Then

[tex]P(X \leq 3) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) = 0.00091 + 0.00638 + 0.02234 + 0.05213 = 0.08176 [/tex]

[tex]P(X > 3) = 1 - P(X \leq 3) = 1 - 0.08176 = 0.91824[/tex]

0.91824 = 91.824% probability that more than 3 students will have their automobiles stolen during the current semester.

free fire op bolte

Step-by-step explanation:

pawri horihe he

9514 1404 393

Answer:

  (4, -15)

Step-by-step explanation:

We assume you want the vertex of ...

  y = x² -8x +1

We can add and subtract 16 to complete the square.

  y = x² -8x +16 +1 -16

  y = (x -4)² -15

Compare to the vertex form ...

  y = (x -h)² +k . . . . . . . quadratic with vertex (h, k)

We see that the vertex of the given function is ...

  (h, k) = (4, -15)

Answer:

x = 4

Step-by-step explanation:

If A is parallel to B, therefore,

9x + 4 = 5x + 20 (alternate interior angles are congruent)

9x + 4 - 5x = 5x + 20 - 5x (subtraction property of equality)

4x + 4 = 20

4x + 4 - 4 = 20 - 4 (subtraction property of equality)

4x = 16

4x/4 = 16/4 (division property of equality)

x = 4

Answer:

At a .05 level of significance, it can be concluded that the mean of the population is significantly more than 3 minutes.

Step-by-step explanation:

We want to test to determine whether or not the mean waiting time of all customers is significantly more than 3 minutes.

At the null hypothesis, we test if the mean is of at most 3 minutes, that is:

[tex]H_0: \mu \leq 3[/tex]

At the alternative hypothesis, we test if the mean is of more than 3 minutes, that is:

[tex]H_1: \mu > 3[/tex]

The test statistic is:

[tex]z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}[/tex]

In which X is the sample mean, [tex]\mu[/tex] is the value tested at the null hypothesis, [tex]\sigma[/tex] is the standard deviation and n is the size of the sample.

3 is tested at the null hypothesis:

This means that [tex]\mu = 3[/tex]

The manager of a grocery store has taken a random sample of 100 customers. The average length of time it took the customers in the sample to check out was 3.1 minutes. The population standard deviation is known to be 0.5 minute.

This means that [tex]n = 100, X = 3.1, \sigma = 0.5[/tex]

Value of the test statistic:

[tex]z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}[/tex]

[tex]z = \frac{3.1 - 3}{\frac{0.5}{\sqrt{100}}}[/tex]

[tex]z = 2[/tex]

P-value of the test and decision:

The p-value of the test is the probability of finding a sample mean above 3.1, which is 1 subtracted by the p-value of z = 2.

Looking at the z-table, z = 2 has a p-value of 0.9772.

1 - 0.9772 = 0.0228

The p-value of the test is of 0.0228 < 0.05, meaning that the is significant evidence to conclude that the mean of the population is significantly more than 3 minutes.

Answer:

one lakh twenty seven thousand and seventy five

I hope this will help you

Answer:

D. y ≤ 2 and y ≤ x

Answer:

D. 6

Step-by-step explanation:

Range of any data set is the difference between the maximum value and the minimum value.

From the graph given above, the least data value plotted on the graph is 1.

Minimum value = 1

The maximum data value = 7

The range of the data set = max - min

Range = 7 - 1

Range = 6

Answer:

31.7919075 % decrease

Step-by-step explanation:

To find the percent decrease

Take the original amount and subtract the new amount

1.73 billion - 1.18 billion =.55 billion

Divide by the original amount

.55 billion / 1.73 billion

.317919075

Change to percent form

31.7919075 % decrease

Answer:

Step-by-step explanation:

the formula attached

Answer: The third one or C

Step-by-step explanation: That is the correct distance formula.

Answer:

the last equation.

Step-by-step explanation:

you would subtract the x values, square them, and add it to the subtracted and squared y values. then take the square root of the remaining value.

Answer:

0.9999985  = 99.99985% probability that in a day, there will be at least 1 birth.

Step-by-step explanation:

In a Poisson distribution, the probability that X represents the number of successes of a random variable is given by the following formula:

[tex]P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}[/tex]

In which

x is the number of sucesses

e = 2.71828 is the Euler number

[tex]\mu[/tex] is the mean in the given interval.

Assume that the mean number of births per day at this hospital is 13.4224.

This means that [tex]\mu = 13.4224[/tex]

Find the probability that in a day, there will be at least 1 birth.

This is:

[tex]P(X \geq 1) = 1 - P(X = 0)[/tex]

In which

[tex]P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}[/tex]

[tex]P(X = 0) = \frac{e^{-13.4224}*13.4224^{0}}{(0)!} = 0.0000015[/tex]

Then

[tex]P(X \geq 1) = 1 - P(X = 0) = 1 - 0.0000015 = 0.9999985 [/tex]

0.9999985  = 99.99985% probability that in a day, there will be at least 1 birth.

Answer:

1

Step-by-step explanation:

1 : 1 :sqrt(2)

The legs are  in the ratio of 1 to 1

tan 45 = opp side / adj side

tan 45 = 1/1

tan 45 =1

Answer:

Step-by-step explanation:

Answer:

1/10

Step-by-step explanation:

any number (1-9) as the number above the fraction line (numerator) with the number 10 below the fraction line is a fraction with a denominator of 10.

if it was 10/10, it will = 1

Answer:

Step-by-step explanation:

H0 : u = 1.0 mg/kg

HA: u > 1.0 mg/kg

Test statistic = -10.09

p-value is approximately 1, would report 0.9999

α = 10% ; 0.1

Using the Pvalue, we can make a decision pattern ;

Recall ; H0 is rejected If Pvalue < α

Here,

Pvalue Given is ' 0.99999 α = 0.1

Pvalue > α ; Hence, we fail to reject the Null ;

The actual Pvalue calculated using the test statistic will be :

Pvalue(-10.09) with test statistic value using a Pvalue calculator

Pvalue < 0.00001

The difference of course is the symbol between the f and g letters.

The circle [tex]\circ[/tex] notation means we're doing a function composition.

Writing [tex](f \circ g)(x)[/tex] is the same as saying [tex]f(g(x))[/tex] where g is the inner function.

Here's an example

f(x) = x^2

g(x) = 3x

f( g(x) ) = ( g(x) )^2 ... note how x is replaced with g(x)

f( g(x) ) = ( 3x )^2

f( g(x) ) = 9x^2

-------------------

On the other hand, the dot notation means we multiply the f(x) and g(x) functions.

Going back to the previous example, we could say

[tex]f(x) = x^2\\\\g(x) = 3x\\\\(f \cdot g)(x) = f(x)*g(x)\\\\(f \cdot g)(x) = x^2*3x\\\\(f \cdot g)(x) = 3x^3\\\\[/tex]

Answer:

1.6 = 1 + .6 = 60% growth rate

Step-by-step explanation:

Answer:

maximum: y = 1

minimum: y = 0.

Step-by-step explanation:

Here we have the function:

y = f(x) =  √(1 + x^2 - 2x)

we want to find the minimum and maximum in the segment [0, 1]

First, we evaluate in the endpoints, which are 0 and 1.

f(0)  =√(1 + 0^2 - 2*0) = 1

f(1) = √(1 + 1^2 - 2*1) = 0

Now let's look at the critical points (the zeros of the first derivate)

To derivate our function, we can use the chain rule:

f(x) = h(g(x))

then

f'(x) = h'(g(x))*g(x)

Here we can define:

h(x) = √x

g(x) = 1 + x^2 - 2x

Then:

f(x) = h(g(x))

f'(x)  =  1/2*( 1 + x^2 - 2x)*(2x - 2)

f'(x) = (1 + x^2 - 2x)*(x - 1)

f'(x) = x^3 - 3x^2 + x - 1

this function does not have any zero in the segment [0, 1] (you can look it in the image below)

Thus, the function does not have critical points in the segment.

Then the maximum and minimum are given by the endpoints.

The maximum is 1 (when x = 0)

the minimum is 0 (when x = 1)

Answer:

B) 1.622 to 1.778 includes the mean of the population beta.

Step-by-step explanation:

We have the standard deviation for the sample, so the t-distribution is used to solve this question.

The first step to solve this problem is finding how many degrees of freedom,which is the sample size subtracted by 1. So

df = 100 - 1 = 99

95% confidence interval

Now, we have to find a value of T, which is found looking at the t table, with 99 degrees of freedom(y-axis) and a confidence level of [tex]1 - \frac{1 - 0.95}{2} = 0.975[/tex]. So we have T = 1.9842

The margin of error is:

[tex]M = T\frac{s}{\sqrt{n}} = 1.9842\frac{0.4}{\sqrt{100}} = 0.078[/tex]

In which s is the standard deviation of the sample and n is the size of the sample.

The lower end of the interval is the sample mean subtracted by M. So it is 1.7 - 0.078 = 1.622.

The upper end of the interval is the sample mean added to M. So it is 1.7 + 0.078 = 1.778.

Thus the correct answer is given by option B.

Answer:

[tex]{ \tt{ \frac{x}{46} = \frac{(39 + 39)}{39} }} \\ x = \frac{46 \times (39 + 39)}{39} \\ x = 92[/tex]

Answer:

it is B (92)

Step-by-step explanation:

best of luck thank

We know, the probability of an event = Favorable outcomes / Total outcomes.

In a case of two dices,

Total outcomes = 6 × 6 = 36

A.T. Q favorable outcome is a sum of 6,

Ways of obtaining a sum of 6

(1,5), (5,1), (2,4),(4,2) and (3,3). Total 5 ways in which 6 can be obtained using two dices.

Therefore, required probability (P),

P = 5/ 36

Answer: 25

Step-by-step explanation:

Answer:

The result indicates that the percentage of all samples of three men that have mean brain weights within (1.24 * sampling error) of the mean is 78.50%.

Step-by-step explanation:

Note: This question is not complete. The complete question is therefore provided before answering the question as follows:

According to one study, brain weights of men are normally distributed with mean = 1.20 kg and a standard deviation = 0.14 kg.

Determine the percentage of all samples of three men that have mean brain weights within 0.1 kg of the population mean brain weight of 1.20 kg. Interpret your answer in terms of sampling error.

The explanation of the answers is now provided as follows:

Based on the Central limit theorem, it possible to say that the mean of sampling distribution (μₓ) is approximately equal to the population mean (μ) as follows:

μₓ = μ = 1.20 kg …………………………. (1)

Also, the standard deviation of the sampling distribution can be written as follows:

σₓ = (σ/√N) ……………………….. (2)

Where:

σ = population standard deviation = 0.14 kg

N = Sample size = 3

Substituting the values into equation (2), we have:

σₓ = 0.14 / √3 = 0.0808

Since we are to determine the percentage of all samples of three men that have mean brain weights within 0.1 kg of the population mean brain weight of 1.20 kg, this implies that we have:

P(1.10 ≤ x ≤ 1.30)

Therefore, 1.10 and 1.30 have to be first normalized or standardized as follows:

For 1.10 kg

z = (x - μₓ) / σₓ = (1.10 - 1.20) / 0.0808 = -1.24

For 1.30 kg

z = (x - μₓ)/σₓ = (1.30 - 1.20) / 0.0808 = 1.24

The required probability can be determined when P(1.10 ≤ x ≤ 1.30) = P(-1.24 ≤ z ≤ 1.24).

From the normal distribution table, the following can be obtained for these probabilities:

P(1.10 ≤ x ≤ 1.30) = P(-1.24 ≤ z ≤ 1.24) = P(z ≤ 1.24) - P(z ≤ -1.24) = 0.89251 - 0.10749 = 0.7850, or 78.50%

Therefore, the sampling error is equal to 0.0808 which is the standard deviation of the sampling distribution.

In terms of the sampling error, the result indicates that the percentage of all samples of three men that have mean brain weights within (1.24 * sampling error) of the mean is 78.50%.

Answer:

Using PEMDAS the answer would be 192758

Step-by-step explanation:

(356*27)+(537*373)-(235*73)=

9612+200301-17155=

Solve

192758

Happy learning!

--Applepi101

Answer:

x = 4

Step-by-step explanation:

[tex]3^{2x+1} = 3^{x+5}[/tex]

if the bases are equal then the powers must be equal as well

2x+ 1 = x+5 export like terms to same side of equation

2x - x = 5 - 1 add/subtract like terms

x = 4

Answer:

0.7 x 10 ^ -9

Step-by-step explanation:

(3.5 x 10 ^ -4) ÷ (5 x 10 ^ 5)

3.5 / 5 x 10 ^ -4/ 10 ^ 5

=> 0.7 x 10 ^ -9

Let X be the random variable representing the weight of a randomly selected widget. You're given that the mean and standard deviation of X (which is normally distributed) are 41 oz and 11 oz, respectively.

Then

Pr[X > 19] = Pr[(X - 41)/11 > (19 - 41)/11] = Pr[Z > -2]

where Z follows the standard normal distribution with mean 0 and s.d. 1.

I assume you're familiar with the 68-95-99.7 rule, the important part of which says that approximately 95% of any normal distribution lies within 2 standard deviations of the mean. Mathematically, this is to say

Pr[-2σ < X < 2σ] ≈ 0.95

where σ is the s.d. of X, or in terms of Z,

Pr[-2 < Z < 2] ≈ 0.95

This means that roughly 5% of the distribution falls outside this range:

Pr[(Z < -2) or (Z > 2)] = 1 - Pr[-2 < Z < 2] ≈ 0.05

and because the distribution is symmetric about its mean, the probability of falling within either tail of the distribution is half of this, or roughly 2.5%

Pr[Z < -2] ≈ 0.05/2 ≈ 0.025

Then the probability of the complement is

Pr[Z > -2] = 1 - Pr[Z < -2] ≈ 1 - 0.025 ≈ 0.975

so that Pr[X > 19] ≈ 97.5%.