Thirty-four college students were asked how much money they spent on textbooks for the current semester. Their responses are shown in the following stemplot.


1 2 3 3 4 5 5 6 7 8
2 1 2 3 4 5 6 8 8 9 9 9
3 1 2 2 7 8 9
4 1 4 5 7
5 1 3
6 2
7
8 1

Key: 1|2 = $120

a. Describe a procedure for identifying potential outliers, and use the procedure to decide whether there are outliers among the responses for the money spent on textbooks.
b. Based on the stemplot, write a few sentences describing the distribution of money spent on textbooks for the 34 students.

Answer:

Step-by-step explanation:

Sample proportion is x/n

Where

p = probability of success

n = number of samples

p = x/n = 63/150 = 0.42

q = 1 - p = 1 - 0.42 = 0.58

To determine the z score, we subtract the confidence level from 100% to get α

Since 1 - α = 0.9

α = 1 - 0.9 = 0.1

α/2 = 0.1/2 = 0.05

This is the area in each tail. Since we want the area in the middle, it becomes

1 - 0.05 = 0.95

The z score corresponding to the area on the z table is 1.645. Thus, confidence level of 90% is 1.645

Confidence interval is written as

(Sample proportion ± margin of error)

Margin of error = z × √pq/n

= 1.645 × √(0.42 × 0.58)/150

= 0.066

The lower end of the confidence interval is

0.42 - 0.066 = 0.354

The upper end of the confidence interval is

0.42 + 0.066 = 0.486

Therefore, the answers to the given questions are

1) d. 0.42

2) the quantity after the ± is the half width. It is also the margin of error. Thus

The half width of this confidence interval is closest to

d. 0.0663

3) c.0.3537

4) b.0.4863

5) d.With 90% confidence, 0.3537 < p < 0.4863

Answer:

30 square inch

Step-by-step explanation:

[tex]area \: of \: base = 6 \times 5 = 30 \: {inch}^{2} \\ [/tex]

Answer:

a. [tex]\mu=\bar x =14.6[/tex]

b. The 95% CI for the population mean is (14.22, 14.98).

c. B. "The statement is incorrect. A correct statement would be​"One can be​ 95% confident that the true mean number of people named per person will fall in the interval computed in part b"

d. D. It does not impact the validity of the interpretation because the sampling space of the sample mean is approximately normal according to the Central Limit Theorem.

Step-by-step explanation:

a) The sample mean provides a point estimation of the population mean.

In this case, the estimation of the mean is:

[tex]\mu=\bar x =14.6[/tex]

b) With the information of the sample we can estimate the

As the sample size n=2824 is big enough, we can aproximate the t-statistic with a z-statistic.

For a 95% CI, the z-value is z=1.96.

The sample standard deviation is s=10.3.

The margin of error of the confidence is then calculated as:

[tex]E=z\cdot s/\sqrt{n}=1.96*10.3/\sqrt{2824}=20.188/53.141=0.38[/tex]

The lower and upper limits of the CI are:

[tex]LL=\bar x-z\cdot s/\sqrt{n}=14.6-0.38=14.22\\\\UL=\bar x+z\cdot s/\sqrt{n}=14.6+0.38=14.98[/tex]

The 95% CI for the population mean is (14.22, 14.98).

c. "95% of the​ time, the true mean number of people named per person will fall in the interval computed in part b"

The right answer is:

B. "The statement is incorrect. A correct statement would be​"One can be​ 95% confident that the true mean number of people named per person will fall in the interval computed in part b"

The confidence interval gives bounds within there is certain degree of confidence that the true population mean will fall within.

It does not infer nothing about the sample means or the sampling distribution. It only takes information from a sample to estimate a interval for the population mean with certain degree of confidence.

d. It is unlikely that the personal network sizes of adults are normally distributed. In​ fact, it is likely that the distribution is highly skewed. If​ so, what​ impact, if​ any, does this have on the validity of inferences derived from the confidence​ interval?

The answer is:

D. It does not impact the validity of the interpretation because the sampling space of the sample mean is approximately normal according to the Central Limit Theorem.

The reliability of a confidence interval depends more on the sample size, not on the distribution of the population. As the sample size increases, the absolute value of the skewness and kurtosis of the sampling distribution decreases. This sample size relationship is expressed in the central limit theorem.

The point estimate for μ is 14.6. The confidence interval will provide the range where the true mean falls with 95% confidence. The Central Limit Theorem suggests that the deviation from the normal distribution will not significantly affect the answers.

a- The point estimate for μ is x=14.6. This is calculated as the mean of all measured values.

b- An interval estimate can be calculated with the formula: x ± Z*(s/√n) where Z is the Z-value from a Z-table corresponding to desired confidence level, here, 0.95. The result would give you the range in which the true mean, μ, falls with 95% confidence.

c- The correct answer is B: The statement is incorrect. A correct statement would be "One can be 95% confident that the true mean number of people named per person will fall in the interval computed in part b."

d- If the personal network sizes of adults are not normally distributed and the distribution is highly skewed, it will have an impact on the validity of inferences derived from the confidence interval. The correct answer is D: It does not impact the validity of the interpretation as the sampling space of the sample mean will still be approximately normal due to the Central Limit Theorem.

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Answer:

[tex]z=\frac{0.54 -0.5}{\sqrt{\frac{0.5(1-0.5)}{1000}}}=2.530[/tex]  

[tex]p_v =P(z>2.530)=0.0057[/tex]  

Step-by-step explanation:

Data given and notation

n=1000 represent the random sample taken

[tex]\hat p=0.54[/tex] estimated proportion of residents that favored the annexation

[tex]p_o=0.5[/tex] is the value that we want to test

z would represent the statistic (variable of interest)

[tex]p_v[/tex] represent the p value (variable of interest)  

Concepts and formulas to use  

We need to conduct a hypothesis in order to test the claim that the true proportion is higher than 0.5:  

Null hypothesis:[tex]p \leq 0.5[/tex]  

Alternative hypothesis:[tex]p > 0.5[/tex]  

When we conduct a proportion test we need to use the z statistic, and the is given by:  

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

The One-Sample Proportion Test is used to assess whether a population proportion [tex]\hat p[/tex] is significantly different from a hypothesized value [tex]p_o[/tex].

Calculate the statistic  

Since we have all the info required we can replace in formula (1) like this:  

[tex]z=\frac{0.54 -0.5}{\sqrt{\frac{0.5(1-0.5)}{1000}}}=2.530[/tex]  

Statistical decision  

It's important to refresh the p value method or p value approach . "This method is about determining "likely" or "unlikely" by determining the probability assuming the null hypothesis were true of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed". Or in other words is just a method to have an statistical decision to fail to reject or reject the null hypothesis.  

The next step would be calculate the p value for this test.  

Since is a right tailed test the p value would be:  

[tex]p_v =P(z>2.530)=0.0057[/tex]  

A deposit of at least $95.75 is needed to avoid the service fee, as this will bring the balance from $204.25 back to the required $300 minimum.

To avoid a service fee, we need to ensure that the checking account balance is at least $300 at the end of the month. Starting with a balance of $337.03 and after spending $132.78, the new balance is calculated as follows:

$337.03 - $132.78 = $204.25.

To avoid the service fee, the account balance must return to at least $300. Therefore, you need to deposit the difference between your current balance and the minimum balance required:

$300 - $204.25 = $95.75.

Any deposit amount greater than or equal to $95.75 will therefore avoid the service fee.

Hey There!

The answer you are looking for is; $6.24!

Work:

You simply add $3.75 + $2.49 together.

Since .75 + .29 = 1.24, you carry the one over to the full dollar.

3 + 2 + 1 = 6.

= 6.24

Hope I helped! 5 stars and brainliest are always appreciated.

Answer:

6.24

Step-by-step explanation:

you add the two numbers

Answer:

102

Step-by-step explanation:

Answer: She should use THE PAIRED SAMPLE T-TEST.

Step-by-step explanation: The Paired sample t-test, is a method used in statistics to determine whether the mean difference in a statistics is zero. Which shows the accuracy of the two different recorded observation.

The paired sample t-test will help her to evaluate the recorded performance rating of the workers before the workshop, and after attending the workshop.

Example:

Let the mean in the workers performance rating before the workshop be Mb, and after the worship be Ma.

If she wants to find how significant the workshop was.

Ma - Mb = 0 means the workshop did not have any influence in their performance, as their performance remains the same.

Ma - Mb > 0 means that the workshop has improved the performance of the workers. As their mean performance after the workshop is greater than their mean performance before the workshop.

Ma - Mb <0 means that the workshop has reduced the performance of the workers. As their mean performance before the workshop is greater than their mean performance after the workshop.

Answer:

The probability that none of the four cans selected contains an incorrect mix of paint is P=0.2545.

Step-by-step explanation:

We have 12 cans, out of which 3 are defective (incorrect mix of paint).

The man will choose 4 cans to paint his mother's house living room.

Let x = the number of the paint cans selected that are defective.

The variable x is known to follow a hypergeometric distribution.

The probability of getting k=0 defectives in a selected sample of K=4 cans, where there are n=3 defectives in the population of N=12 cans is:

[tex]P(X=k)=\dfrac{\binom{K}{k}\binom{N-K}{n-k}}{\binom{N}{n}}\\\\\\\\ P(X=0)=\dfrac{\binom{4}{0}\binom{12-4}{3-0}}{\binom{12}{3}}=\dfrac{\binom{4}{0}\binom{8}{3}}{\binom{12}{3}}=\dfrfac{1*56}{220}=\dfrac{56}{220}=0.2545[/tex]

The probability that none of the four cans selected contains an incorrect mix of paint is P=0.2545.

Final answer:

The probability that none of the four randomly selected cans are defective is approximately 0.2545, or 25.45%, which is determined using the hypergeometric distribution.

Explanation:

The student is faced with a scenario where a man has twelve 1-gallon paint cans, out of which three contain an incorrect mix of paint. The man randomly selects four of these cans to paint with, and the question is to find the probability that none of the four selected cans are defective, which follows the hypergeometric distribution.

The relevant parameters for the hypergeometric distribution in this scenario are: the total number of cans (N=12), the number of defective cans (K=3), the number of cans selected (n=4), and the number of defective cans selected that we are interested in (x=0). To compute the probability, we use the hypergeometric probability formula:

P(X = x) = [(C(K, x) * C(N-K, n-x)) / C(N, n)]

Substituting the given values, we have:

P(X = 0) = [(C(3, 0) * C(12-3, 4-0)) / C(12, 4)]
= [(1 * C(9, 4)) / C(12, 4)]
= (1 * 126) / 495
≈ 0.2545

This means the probability that none of the four randomly selected cans are defective is approximately 0.2545, or 25.45%.

Answer:

A. We are 90% confident that the interval from nothing to nothing actually contains true mean attractiveness rating of all adult females.

Step-by-step explanation:

The population is set of items which are similar in nature and that are to be observed for an outcome. The Confidence Interval is a defined probability that the parameters lies in this range. Population parameter is quantity which enters in probability distribution of random variable. In the given question the confidence interval is 90% which means the parameters lies within this range.

Answer:

To Prove: [tex]9e^x[/tex] is equal to the sum of its Maclaurin series.

Step-by-step explanation:

If [tex]f(x) = 9e^x[/tex], then [tex]f ^{(n + 1)(x)} =9e^x[/tex] for all n. If d is any positive number and   |x| ≤ d, then [tex]|f^{(n + 1)(x)}| = 9e^x\leq 9e^d.[/tex]

So Taylor's Inequality, with a = 0 and M = [tex]9e^d[/tex], says that [tex]|R_n(x)| \leq \dfrac{9e^d}{(n+1)!} |x|^{n + 1} \:for\: |x| \leq d.[/tex]

Notice that the same constant [tex]M = 9e^d[/tex] works for every value of n.

But, since [tex]lim_{n\to\infty}\dfrac{x^n}{n!} =0 $ for every real number x$[/tex],

We have [tex]lim_{n\to\infty} \dfrac{9e^d}{(n+1)!} |x|^{n + 1} =9e^d lim_{n\to\infty} \dfrac{|x|^{n + 1}}{(n+1)!} =0[/tex]

It follows from the Squeeze Theorem that [tex]lim_{n\to\infty} |R_n(x)|=0[/tex] and therefore [tex]lim_{n\to\infty} R_n(x)=0[/tex] for all values of x.

[tex]THEOREM\\If f(x)=T_n(x)+R_n(x), $where $T_n $is the nth degree Taylor Polynomial of f at a and $ lim_{n\to\infty} R_n(x)=0 \: for \: |x-a|<R, $then f is equal to the sum of its Taylor series on $ |x-a|<R[/tex]

By this theorem above, [tex]9e^x[/tex] is equal to the sum of its Maclaurin series, that is,

[tex]9e^x=\sum_{n=0}^{\infty}\frac{9x^n}{n!}[/tex]  for all x.

The question asks to perform a hypothesis test about the mean pH level in a river. Given a sample size of 29, a sample mean of 6.7, a sample standard deviation of 0.35, and a significance level of α = 0.05, the provided reference suggests that there is insufficient evidence to reject the company's claim of a mean pH of 6.8, due to the calculated p-value being greater than α.

In this problem, we are testing the hypothesis that the mean pH level of water in a nearby river is 6.8. The company claims this as the true population mean. The hypothesis under test is called the Null hypothesis.

The level of significance is given as α = 0.05. We have a sample of size 29 with mean 6.7 and standard deviation 0.35.

In hypothesis testing, we calculate a test statistic and compare it with a critical value corresponding to the level of significance α. Here, we would be calculating a t-score because we have the sample standard deviation, not the population standard deviation and the sample size is less than 30. If the test statistic falls in the critical region, then we reject the null hypothesis.

Without specific calculations, the given reference suggests that the decision is to not reject the null hypothesis, citing p-value > α. In this case, the calculated p-value from testing statistics is higher than 0.05, meaning that the observed test statistic would be quite likely if the null hypothesis is true.

This results in the conclusion that there is insufficient evidence in the sampled data to reject the company's claim of a mean pH of 6.8.

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There is not enough evidence to reject the company's claim at the α=0.05 level of significance.

Given:

Population mean =6.8

Sample mean  =6.7

Sample standard deviation s=0.35

Sample size n=29

Level of significance α=0.05

We'll perform a one-sample t-test since the population standard deviation is unknown and the sample size is less than 30.

The hypotheses are:

Null hypothesis (o):

The mean pH level of the water in the river is 6.8 (μ=6.8).

Alternative hypothesis (H1):

The mean pH level of the water in the river is not equal to 6.8 (≠6.8)

We'll use the formula for the test statistic of a one-sample t-test:

t = (x-  ) / [tex]\frac{s}{\sqrt{n} }[/tex]

t= -0.1/ 0.0651

t≈−1.535

Now, we'll find the critical value for a two-tailed test at α=0.05 significance level with n−1=28 degrees of freedom. Using a t-distribution table or statistical software,

we find the critical values to be approximately ±2.048.

Since −1.535 falls within the range −2.048 to 2.048, we fail to reject the null hypothesis.

So, there is not enough evidence to reject the company's claim at the α=0.05 level of significance.

Answer:

there is 60 minutes in a day or in a hour?

according to 60 min in a hour

Answer: 24*60= 1440 min

Step-by-step explanation:

its impossible to have 60 min in a day.

There are 1440 minutes in a 24 hour day. You can find this by multiplying the number of hours (24) by the number of minutes in an hour (60).

The subject of your question is related to the conversion of units of time. In this case, you want to convert hours into minutes. We know that one hour is equivalent to 60 minutes. Hence, if we want to find out how many minutes are there in a 24 hour day, we will multiply the number of hours (24) by the conversion factor, which is 60 minutes per hour.

So, 24 hours * 60 minutes/hour = 1440 minutes. Therefore, there are 1440 minutes in a 24 hour day. It's straightforward when you use correct conversion factor properly.

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Answer:

32 ounces

Step-by-step explanation:

She bought 1 cucumber. She bought twice as much lettuce.

1(2) = 2 lbs of lettuce.

There are 16 ounces to the lb.

2 (16 ounces) = 32 ounces

Answer:

She bought 32 oz of lettuce.

Step-by-step explanation:

There are 16 oz in 1 lb. twice as much means 2x. 2 x 16 = 32.

The P-value for this hypothesis test is 0.0228.

To find the P-value for this hypothesis test, we need to calculate the proportion of alumni who favored firing the coach in the sample. Out of 100 alumni, 64 were in favor. So, the sample proportion is 64/100 = 0.64.

Now, we need to calculate the test statistic, which follows a normal distribution. The formula for the test statistic is: z = (p' - p) / sqrt(p * (1-p) / n), where p' is the sample proportion, p is the claimed proportion under the null hypothesis, and n is the sample size.

Plugging in the values, we get: z = (0.64 - 0.50) / sqrt(0.50 * (1-0.50) / 100) = 2.00

The P-value is the probability of observing a test statistic as extreme as 2.00, assuming the null hypothesis is true. We can look up this probability in a standard normal distribution table or use a statistical software. In this case, the P-value is 0.0228.

Answer:

66 and 114 degrees

Step-by-step explanation:

Supplementary angles add to 180 degrees.

An angle measures 48 more than its supplementary angle. If the supplementary angle is x, then the other angle must be x+48

x+x+48=180

Subtract 48 from both sides

x+x+48-48=180-48

x+x=132

Combine like terms

2x=132

Divide both sides by 2

2x/2=132/2

x=66

So, one of the angles is 66 degrees. The other is x+48

x+48

66+48=114

One of the angles is 66 degrees, the other is 114 degrees

Answer:

96

Step-by-step explanation:

Answer:

BC = 9

Step-by-step explanation:

Assuming this is a straight line

AB + BC = AC

2x-6 + x+2 = 17

Combine like terms

3x -4 = 17

Add 4 to each side

3x-4+4 = 17+4

3x = 21

Divide each side by 3

3x/3 =21/3

x =7

We want to find BC

BC =x+2

     =7+2

     =9

To decompose the fraction 2 3/4, convert it to an improper fraction by multiplying the whole number by the denominator of the fraction, add the numerator, and place over original denominator, resulting in 11/4.

The question asks to decompose the fraction 2 3/4 into its components. To decompose this mixed number, we need to convert it to an improper fraction. The process involves multiplying the whole number by the denominator of the fraction part, adding the numerator of the fraction part, and then placing the result over the original denominator.

Therefore, the mixed number 2 3/4 decomposed into an improper fraction is 11/4.

Answer:

a) 0.214 or 21.4%

b) P=0.011

c) The realtor should sample at least 551 homes.

Step-by-step explanation:

The current thinking is that housing prices follow an approximately normal model with mean $238,000 and standard deviation $5,041.

a) We need to know the proportion of housing prices in Athens that are less than $234,000. We can calculate this from the z-score for the population distribution.

[tex]z=\dfrac{X-\mu}{\sigma}=\dfrac{234,000-238,000}{5,041}=\dfrac{-4,000}{5.041}=-0.793\\\\\\ P(x<234,000)=P(z<-0.793)=0.214[/tex]

The proportion of housing prices in Athens that are less than $234,000 is 0.214.

b) Now, a sample is taken. The size of the sample is n=134.

We have to calculate the probability that the average selling price is greater than $239,000.

In this case, we have to use the standard error of the sampling distribution to calculate the z-score:

[tex]z=\dfrac{\bar x-\mu}{\sigma/\sqrt{n}}=\dfrac{239,000-238,000}{5,041/\sqrt{134}}=\dfrac{1,000}{435.476}= 2.296 \\\\\\P(\bar x>239,000)=P(z>2.296)=0.011[/tex]

The probability that the average selling price is greater than $239,000 is 0.011.

c) We have another sample taken from a distribution with the same parameters.

We have to calculate the sample size so that the margin of error for a 98% confidence interval is $500.

The expression for the margin of error of the confidence interval is:

[tex]E=z\cdot \sigma/\sqrt{n}[/tex]

We can isolate n from the margin of error equation as:

[tex]E=z\cdot \sigma/\sqrt{n}\\\\\sqrt{n}=\dfrac{z\cdot \sigma}{E}\\\\n=(\dfrac{z\cdot \sigma}{E})^2[/tex]

We have to look for the critical value of z for a 98% CI. This value is z=2.327.

Now we can calculate the minimum value for n to achieve the desired precision for the interval:

[tex]n=(\dfrac{z\cdot \sigma}{E})^2\\\\\\n=(\dfrac{2.327*5,041}{500})^2= 23.461 ^2=550.410\approx551[/tex]

The realtor should sample at least 551 homes.

Answer:

a) 0.214 or 21.4%

b) P=0.011

c) The realtor should sample at least 551 homes

Step-by-step explanation:

Answer:

0.7

Step-by-step explanation:

0.3+0.7=1.0=100%

Final answer:

The probability of not winning the game that Martin is playing is 0.7 or 70%, which is obtained by subtracting the probability of winning (0.3) from 1.

Explanation:

If Martin is playing a game where the probability of winning is 0.3, then the probability of not winning can be calculated by subtracting the probability of winning from 1. This is because the sum of the probabilities of all possible outcomes must equal 1. Since the probability of winning is 0.3, we calculate the probability of not winning as follows:

Therefore, the probability of not winning is 0.7 or 70%.

Answer:

To find why the crimes were committed

Answer:

y =20

Step-by-step explanation:

5(y+4)=6y

Distribute

5y +20 = 6y

Subtract 5y from each side

5y-5y+20=6y-5y

20 =y

Answer:

solution

5y+20=6y

5y-6y=20

-y=20

Answer:

Let's assume the following data:

Price in Dollars (X) 26 29 32 38 47

Number of Bids (Y) 12 13 15 16 18

For our case we have this:

n=10 [tex] \sum x = 172, \sum y = 74, \sum xy = 2623, \sum x^2 =6194, \sum y^2 =1118[/tex]  

[tex]r=\frac{5(2623)-(172)(74)}{\sqrt{[5(6194) -(172)^2][5(1118) -(74)^2]}}=0.974[/tex]  

So then the correlation coefficient would be r =0.974

Step-by-step explanation:

Previous concepts

The correlation coefficient is a "statistical measure that calculates the strength of the relationship between the relative movements of two variables". It's denoted by r and its always between -1 and 1.

Solution to the problem

And in order to calculate the correlation coefficient we can use this formula:  

[tex]r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}[/tex]  

Let's assume the following data

Price in Dollars (X) 26 29 32 38 47

Number of Bids (Y) 12 13 15 16 18

For our case we have this:

n=10 [tex] \sum x = 172, \sum y = 74, \sum xy = 2623, \sum x^2 =6194, \sum y^2 =1118[/tex]  

[tex]r=\frac{5(2623)-(172)(74)}{\sqrt{[5(6194) -(172)^2][5(1118) -(74)^2]}}=0.974[/tex]  

So then the correlation coefficient would be r =0.974

Answer:

3 nights

Step-by-step explanation:

because 1 flight there and one flight back =300 then add 3 nights =480

Answer:

5 nights or less

Step-by-step explanation:

You can do this by writing an inequality and solving it.

Let n = number of nights.

1 hotel night costs $60. n number of hotel nights cost 60n.

The flight costs $150.

The total cost is the price of the hotel plus the price of the flight.

60n + 150

The total price must be less than or equal to $500.

[tex] 60n + 150 \le 500 [/tex]

Now we solve the inequality.

Subtract 150 from both sides.

[tex] 60n \le 350 [/tex]

Divide both sides by 60.

[tex] n \le \dfrac{350}{60} [/tex]

350 divided by 60 is 5.8333...

[tex] n \le 5.8 [/tex]

The number of night is less than or equal to 5.8, and it must be a whole number, so the most number of nights she can afford is 5.

To find the minimum score needed to receive a grade of A, we need to determine the cutoff point for the top 16.6% of students. We can use the Z-score formula to convert a raw score into a standardized score and then find the corresponding raw score. The minimum score needed to receive a grade of A is approximately 88.

To find the minimum score needed to receive a grade of A, we need to determine the cutoff point for the top 16.6% of students. In a normal distribution, we can use the Z-score formula to convert a raw score into a standardized score. We need to find the Z-score that corresponds to the 83.4th percentile, as 16.6 percent is the area to the left of this score. We can then use the Z-score formula to find the corresponding raw score.

Z = (X - μ) / σ

Where: Z is the Z-score, X is the raw score, μ is the mean, and σ is the standard deviation. Rearranging the formula, we have:

X = (Z * σ) + μ

Since the mean is 78 and the standard deviation is 10, we substitute the values into the formula:

X = (Z * 10) + 78

Next, we need to find the Z-score that corresponds to the 83.4th percentile using a Z-score table or a calculator. From the table, we find that the Z-score is approximately 0.9998. Substituting this value into the formula, we can solve for X:

X = (0.9998 * 10) + 78

X = 9.998 + 78

X ≈ 87.998

Therefore, the minimum score needed to receive a grade of A is approximately 88.

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Answer:

32$

Step-by-step explanation:

first divide 80 by 5.

(you should get 16)

next multiply by 2

(you should get 32)

this works because out of the 80$ he spent 2/5 of his money. you basically are multiplying the numerators and then dividing by the denominators and because 80 is a whole number it works without having to use the 1.

another way to do it is multiply 80/1 by 2/5

you should get 160/5 and when you simplify you should get 32

Jay spent $32 on new running shoes, which is calculated by taking 2/5 of his original $80.

The solution can be solved as: Jay had $80 and spent 2/5 of his money on new running shoes. To find out how much Jay spent, we need to calculate 2/5 of $80.

First, we divide $80 by 5 to find out how much 1/5 of his money is:

1/5 of $80 = $80 / 5 = $16

Now, we multiply this amount by 2 to get 2/5:

2/5 of $80 = 2 x $16 = $32

So, Jay spent $32 on new running shoes.

Answer:

temperature on the beach = T2 = 34.56 °C

Step-by-step explanation:

We are given;

P1 = 4.5 atm

T1 = 24 °C = 24 + 273 = 297 K

P2 = 4.66 atm

Thus, P1/T1 = P2 /T2

So, T2 = P2•T1/P1

Thus, T2 = (4.66x 297)/4.5

T2 = 307.56 K

Let's convert to °C to obtain ;

T2 = 307.56 - 273

T2 = 34.56 °C

Answer:

The p-value for the test of hypothesis is P(z<-3.617)=0.0002.

Step-by-step explanation:

Hypothesis test on the difference between proportions.

The claim is that the percent of males who are underclassmen stats students (π1) is less than the percent of females who are underclassmen stats students (π2).

Then, the null and alternative hypothesis are:

[tex]H_0: \pi_1-\pi_2=0\\\\H_a:\pi_1-\pi_2<0[/tex]

The male sample has a size n1=156. The sample proportion is p1=81/156=0.52.

The female sample has a size n2=221. The sample proportion in this case is p2=221/320=0.69.

The weigthed average of proportions p, needed to calculate the standard error, is:

[tex]p=\dfrac{n_1p_1+n_2p_2}{n_1+n_2}=\dfrac{81+221}{156+320}=\dfrac{302}{476}= 0.63[/tex]

The standard error for the difference in proportions is:

[tex]\sigma_{p1-p2}=\sqrt{\dfrac{p(1-p)}{n_1}+\dfrac{p(1-p)}{n_2}}=\sqrt{\dfrac{0.63*0.37}{156}+\dfrac{0.63*0.37}{320}}\\\\\\\sigma_{p1-p2}=\sqrt{\dfrac{0.2331}{156}+\dfrac{0.2331}{320}}=\sqrt{0.001503871+0.000728438}=\sqrt{0.002232308}\\\\\\\sigma_{p1-p2}=0.047[/tex]

Then, we can calculate the z-statistic as:

[tex]z=\dfrac{p_1-p_2}{\sigma_{p1-p2}}=\dfrac{0.52-0.69}{0.047}=\dfrac{-0.17}{0.047}=-3.617[/tex]

The P-value for this left tailed test is:

[tex]P-value = P(z<-3.617)=0.00015[/tex]

Answer:

[tex]z=\frac{0.519-0.691}{\sqrt{0.634(1-0.634)(\frac{1}{156}+\frac{1}{320})}}=-3.657[/tex]    

[tex]p_v =P(Z<-3.657)=0.0001[/tex]  

Step-by-step explanation:

Data given and notation  

[tex]X_{1}=81[/tex] represent the number of males underclassmen

[tex]X_{2}=221[/tex] represent the number of females underclassmen

[tex]n_{1}=156[/tex] sample of male

[tex]n_{2}=320[/tex] sample of female

[tex]p_{1}=\frac{81}{156}=0.519[/tex] represent the proportion of males underclassmen

[tex]p_{2}=\frac{221}{320}= 0.691[/tex] represent the proportion of females underclassmen

z would represent the statistic (variable of interest)  

[tex]p_v[/tex] represent the value for the test (variable of interest)  

Concepts and formulas to use  

We need to conduct a hypothesis in order to check if the percent of males who are underclassmen stats students is less than the percent of females who are underclassmen stats students   , the system of hypothesis would be:  

Null hypothesis:[tex]p_{1} \geq p_{2}[/tex]  

Alternative hypothesis:[tex]p_{1} < p_{2}[/tex]  

We need to apply a z test to compare proportions, and the statistic is given by:  

[tex]z=\frac{p_{1}-p_{2}}{\sqrt{\hat p (1-\hat p)(\frac{1}{n_{1}}+\frac{1}{n_{2}})}}[/tex]   (1)  

Where [tex]\hat p=\frac{X_{1}+X_{2}}{n_{1}+n_{2}}=\frac{81+221}{156+320}=0.634[/tex]  

Calculate the statistic  

Replacing in formula (1) the values obtained we got this:  

[tex]z=\frac{0.519-0.691}{\sqrt{0.634(1-0.634)(\frac{1}{156}+\frac{1}{320})}}=-3.657[/tex]    

Statistical decision

For this case we don't have a significance level provided [tex]\alpha[/tex], but we can calculate the p value for this test.    

Since is a one side test the p value would be:  

[tex]p_v =P(Z<-3.657)=0.0001[/tex]  

Answer:

$834.8 dollars that week

Step-by-step explanation:

All you have to do is multiply $20.87 by 10 hours to get your answer:)

By multiplying Harper's hourly wage ($20.87) by 40 hours, we determined that Harper will earn $834.80 in a 40-hour workweek.

To calculate how much Harper will earn in a 40-hour work week, you simply need to multiply his hourly wage by the number of hours he works. In this case, that's $20.87 times 40. Using direct multiplication:

$20.87 x 40 = $834.80

So, Harper will earn $834.80 in a 40-hour workweek.

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Step-by-step explanation: Please see the attachments below