What is the range of the data below?
50
60
70
80
90
100
A(22)
B(28)
C(41)
D(42)

Answer:

Step-by-step explanation:

Labor: 40.55 x 4 = $162.20 for total Labor.

Total Charges: 25.75 + 38.75 + 162.20 = $226.70 Total charges.

Answer:

The lower limit of the confidence interval is 55%, which is above 50%, so the Republican should expect to win.

Step-by-step explanation:

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

These bounds depend on the sample proportion and the margin of error.

The lower bound is the sample proportion subtracted by the margin of error.

The upper bound is the margin of error added to the sample proportion.

In this problem, we have that:

Sample proportion 59%

Margin of error 4%

59 - 4 = 55%

59 + 4 = 63%

The lower limit of the confidence interval is 55%, which is above 50%, so the Republican should expect to win.

Final answer:

The Republican candidate can neither be certain of victory nor of defeat based on the poll with a margin of error of 3 percentage points. The poll suggests a favorable leaning towards the Republican, but the actual support could range from 53% to 59%, implying the election could be close. Historical examples illustrate that polls are not foolproof predictors of election outcomes.

Explanation:

Whether the Republican candidate should expect to win based on a poll showing 56​% favoritism with a margin of error of 3 percentage points cannot be said with certainty. The margin of error indicates that the true support could theoretically range from 53% to 59%.

To understand the implication, consider that if the candidate's actual support is at the lower end of the margin of error (53%), then it is possible that the race is very close, depending on the percentage of voters favoring the Democratic candidate. If the Democratic candidate has close to 47% support, the election could go either way. Conversely, if the Republican candidate's support is at the higher end (59%), then it is more likely, though not guaranteed, that the Republican would win. Polls provide a snapshot of voter preferences at a particular time and have limitations, including potential sampling errors, nonresponse bias, and inability to predict who will actually turn out to vote.

Historical polls and election outcomes show that while polls can be predictive, they are not always accurate reflections of election results. An example is the 2000 election between George W. Bush and Al Gore, which was a toss-up based on polls but ended with a narrow victory. Similarly, in a hypothetical situation where a state's population is largely liberal, a conservative might still win if the liberal vote is split between two candidates.

Answer:

We have sufficient evidence to support the claim that the average for the students at Jenna's large high school is greater than 94 minutes.

Step-by-step explanation:

Jenna claims that the average time of texting at her larger high school is greater than 94 minutes per day.

From here we can see that we have to perform a hypothesis test about a sample mean. The null and alternate hypothesis will be:

Null Hypothesis: [tex]\mu \leq 94[/tex]

Alternate Hypothesis: [tex]\mu > 94[/tex]

Jenna collected data from a sample of 32 students. So, sample size will be:

Sample Size = n = 32

Sample Mean = x = 96.5

Sample Standard Deviation = s = 6.3

We have to perform a hypothesis test, to test Jenna's claim. Since, the value of Population Standard Deviation is unknown and the value of Sample Standard Deviation is known, we will use One Sample t-test in this case.

The formula to calculate the test statistic is:

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

Using the values, we get:

[tex]t=\frac{96.5-94}{\frac{6.3}{\sqrt{32} } }=2.245[/tex]

The degrees of freedom will be:

df = n - 1 = 32 - 1 = 31

We have to convert the t-score 2.245 with 31 degrees of freedom to its equivalent p-value. From t-table this value comes out to be:

p-value = 0.0160

The significance level is:

[tex]\alpha =0.05[/tex]

Since, the p-value is lesser than the level of significance, we reject the Null Hypothesis.

Conclusion:

We have sufficient evidence to support the claim that the average for the students at Jenna's large high school is greater than 94 minutes.

This p value the significant level  0.05 is given which is higher then the obtained p value. Thus we can reject the null hypothesis. Thus we have convincing statistical evidence to support Jenna’s claim.

Given-

Jenna claims that the average for the students at her large high school is greater than 94 minutes. The null hypothesis is  [tex]\mu\leq 94[/tex]  and alternate hypothesis  [tex]\mu >94[/tex].

Now given that,

The value of sample size [tex]n[/tex] is 32, sample means [tex]x[/tex] is 96.5 and the sample standard deviation [tex]s[/tex] is 6.3.

Here one-sample t-test will be used for the as sample standard deviation is given. The formula for the test statics is,

[tex]t=\dfrac{x-\mu}{\dfrac{s}{\sqrt{n}} }[/tex]

[tex]t=\dfrac{96.5-94}{\dfrac{6.3}{\sqrt{32}} }[/tex]

[tex]t=2.245[/tex]

Now the degrees of freedom is n-1. thus,

[tex]D_f=n-1[/tex]

[tex]D_f=32-1=31[/tex]

Now from the t table the value of t score 2.245 having degree 31 is,

p value[tex]=0.0160[/tex]

For this p value the significant level  0.05 is given which is higher then the obtained p value. Thus we can reject the null hypothesis. Thus we have convincing statistical evidence to support Jenna’s claim.

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Answer:

.54444 = .54444/1 = 5.4444/10 = 54.444/100 = 544.44/1000 = 5444.4/10000 = 54444/100000, any one of those works

Answer:

54/99

Step-by-step explanation:

Answer:

The standard deviation of the number of runs required is 2447.26

Step-by-step explanation:

For each run, there are only two possible outcomes. Either the program fails, or it does not. The probability of the computer failing during a run is independent of other runs. So we use the binomial probability distribution to solve this question.

Binomial probability distribution

Probability of exactly x sucesses on n repeated trials, with p probability.

The standard deviation for the expected number of trials for r sucesses is:

[tex]\sqrt{V(X)} = \sqrt{\frac{r(1-p)}{p^{2}}}[/tex]

A computer program has a bug that causes it to fail once in every thousand runs, on average.

This means that [tex]p = \frac{1}{1000} = 0.001[/tex]

In an effort to find the bug, independent runs of the program will be made until the program has failed six times. What is the standard deviation of the number of runs required?

This means that r = 6. So

[tex]\sqrt{V(X)} = \sqrt{\frac{6*0.999}{(0.001)^{2}}} = 2447.26[/tex]

The standard deviation of the number of runs required is 2447.26

Answer:

x = 5/3

y = 14/3

Step-by-step explanation:

y=4x−2

y=x+3

​Since they are both equal to y, we can set them equal to each other

4x-2 = x+3

Subtract x from each side

4x-2-x = x+3-x

3x-2 =3

Add 2 to each side

3x-2+2 = 3+2

3x =5

Divide each side by 3

3x/3 =5/3

x = 5/3

Now we need to find y

y = x+3

y =5/3+3

y = 5/3+9/3

y = 14/3

Answer:

x=5/3; y=14/3

Step-by-step explanation:

Subtract the following:

-4x+y=-2

-x+y=3

= -3x=-5

x=5/3

substitute x into one of the given equations.

y=5/3+3

y= 14/3

Answer:

Null Hypothesis, [tex]H_0[/tex] : [tex]\mu[/tex] = $9

Alternate Hypothesis, [tex]H_A[/tex] : [tex]\mu[/tex] > $9

Step-by-step explanation:

We are given that a report on a certain fast food restaurant states that μ, the mean order total, is $9. The manager of the restaurant believes the mean is higher.

A random sample of orders will be selected. The sample mean x¯ will be calculated and used in a hypothesis test to investigate the belief.

Let [tex]\mu[/tex] = the mean order total

So, Null Hypothesis, [tex]H_0[/tex] : [tex]\mu[/tex] = $9

Alternate Hypothesis, [tex]H_A[/tex] : [tex]\mu[/tex] > $9

Here, null hypothesis states that  the mean order total is equal to $9 and the manager claim's is not correct.

On the other hand, alternate hypothesis states that  the mean order total is higher than $9 and the manager claim's is correct.

So, this would be the correct set of hypotheses for testing.

Based on the null hypothesis, the mean order to total is $9, and the manager's belief is wrong. Based on alternate hypothesis, the mean order total is more than $9, and the manager is right.

Given information:

A report on a certain fast food restaurant states that μ, the mean order total, is $9.

The manager of the restaurant believes the mean is higher.

So, according to the null hypothesis, [tex]H_0[/tex]

[tex]\mu=9[/tex]

And, according to alternate hypothesis, [tex]H_a[/tex]

[tex]\mu>9[/tex]

Therefore, based on the null hypothesis, the mean order to total is $9, and the manager's belief is wrong. Based on alternate hypothesis, the mean order total is more than $9, and the manager is right.

For more details about null hypothesis, refer to the link:

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Vowels are defined as sound repeated as a, e, i, o, u and the rest 21 letters are classified as consonants.

The given words are generated from English alphabet as a combination of Vowels and alphabets. Thus the combination of vowels and consonant help in the formation of words. There are n number of unique letters are formed.

1) Speed is fast = SPEEFAS

2) Minimum number of participants = MINIPART

3) Sum of excess = SUMCESS

Learn more about combination click;

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To find the number of unique words that can be generated with a given word length and maximum number of consecutive vowels, multiply the number of possible vowel arrangements by the number of possible consonant arrangements.

To determine the number of unique words that can be generated given the length of a word (wordLen) and the maximum number of consecutive vowels (maxVowels), we need to consider the different possibilities for the arrangement of vowels and consonants in the word. Since vowels can be repeated consecutively up to maxVowels times, we can have up to maxVowels + 1 vowels in a row in any word. Similarly, we can have up to wordLen - maxVowels + 1 consonants in a row in any word. Therefore, the total number of unique words that can be generated is (maxVowels + 1) * (wordLen - maxVowels + 1).

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Final answer:

To calculate the labourer's pay for 22 days, divide the total pay for 5 days by 5 to get the daily wage, and then multiply this by 22. The labourer would earn #4400 for 22 days of work.

Explanation:

The question posed is regarding the calculation of a laborer's pay for a certain number of days based on a known daily wage rate.

If a labourer is paid #1000 for 5 days work, to find out his pay for 22 days work we follow these steps:

In conclusion, the labourer's pay for 22 days of work would be #4400.

Answer:

[tex]\chi^2 =\frac{4-1}{0.7^2} 1.5^2 =13.776[/tex]

[tex]p_v =P(\chi^2 >13.776)=0.0032[/tex]

In order to find the p value we can use the following code in excel:

"=1-CHISQ.DIST(13.776,3,TRUE)"

If we compare the p value and the significance level assumed we see that [tex]p_v <\alpha[/tex] so on this case we have enough evidence in order reject the null hypothesis. And we can conclude that the true deviation i significantly higher than 0.7

Step-by-step explanation:

Notation and previous concepts

A chi-square test is "used to test if the variance of a population is equal to a specified value. This test can be either a two-sided test or a one-sided test. The two-sided version tests against the alternative that the true variance is either less than or greater than the specified value"

[tex]n=4[/tex] represent the sample size

We can calculate the sample deviation with this formula:

[tex]s = \sqrt{\frac{\sum_{i=1}^n (X_i -\bar X)^2}{n-1}}[/tex]

[tex]\alpha[/tex] represent the confidence level  

[tex]s =1.5 [/tex] represent the sample variance obtained

[tex]\sigma^2 =0.7[/tex] represent the value that we want to test

Null and alternative hypothesis

On this case we want to check if the population deviation is higher than 0.7, so the system of hypothesis would be:

Null Hypothesis: [tex]\sigma \leq 0.7[/tex]

Alternative hypothesis: [tex]\sigma >0.7[/tex]

Calculate the statistic  

For this test we can use the following statistic:

[tex]\chi^2 =\frac{n-1}{\sigma^2_0} s^2[/tex]

And this statistic is distributed chi square with n-1 degrees of freedom. We have eveything to replace.

[tex]\chi^2 =\frac{4-1}{0.7^2} 1.5^2 =13.776[/tex]

Calculate the p value

In order to calculate the p value we need to have in count the degrees of freedom , on this case 3. And since is a right tailed test the p value would be given by:

[tex]p_v =P(\chi^2 >13.776)=0.0032[/tex]

In order to find the p value we can use the following code in excel:

"=1-CHISQ.DIST(13.776,3,TRUE)"

Conclusion

If we compare the p value and the significance level assumed we see that [tex]p_v <\alpha[/tex] so on this case we have enough evidence in order reject the null hypothesis. And we can conclude that the true deviation i significantly higher than 0.7

Answer:

40 and 1/2

Step-by-step explanation:

Multiply 4 1/2 by 1 1/2. Then multiply the product of 4 1/2 and 1 1/2 by 6.

I believe the answer is 21

21 × 6 = 126

and both numbers are divisible by 3

Answer:

b) False

Calculated value Z  =  1.635 < 1.96 at 0.05 level of significance.

The null hypothesis is accepted.

Step-by-step explanation:

Explanation:-

Step:- (1)

Given data the opinion poll recently sampled 1500 voting age citizens.

Given sample size 'n' = 1500

Given data the opinion poll recently sampled 1500 voting age citizens in selected 1020 of the sampled citizens were in favor of an increase in cigarette taxes.

The sample proportion[tex]'p' = \frac{1020}{1500} = 0.68[/tex]

Given data the state government would like to decide if there is enough evidence to establish whether the proportion of citizens supporting an increase in cigarette taxes is significantly greater than .66

Population proportion 'P' =0.66

                                      Q  = 1-P

                                      Q = 1-0.66 = 0.34

Null hypothesis :H₀: 'P' >0.66

Alternative hypothesis: H₀: 'P' <0.66

Level of significance ∝=0.05

Step:-(2)

The test statistic

                             [tex]Z = \frac{p-P}{\sqrt{\frac{PQ}{n} } }[/tex]

                            [tex]Z = \frac{0.68-0.66}{\sqrt{\frac{0.66 X 0.34}{1500} } }[/tex]

                            Z  =  1.635

The calculated value   Z  =  1.635

The tabulated value Z = 1.96 at ∝=0.05 level of significance.

Therefore  Z  =  1.635 < 1.96 at 0.05 level of significance.

The null hypothesis is accepted.

The alternative hypothesis is rejected.

Conclusion:-

The null hypothesis is accepted at 0.05 level of significance.

The proportion of citizens supporting an increase in cigarette taxes is significantly greater than .66

Answer:

if you divide 80 and 5 would give you 16

Step-by-step explanation:

Answer:

Step-by-step explanation:

Answer: b

Step-by-step explanation:

The solutions to the quadratic equation x^2 = -5x - 3 are (-5 - sqrt(13))/2 and (-5 + sqrt(13))/2, calculated using the quadratic formula -b ± √(b² - 4ac) / (2a).

The subject of this question is Mathematics, specifically, the solution of quadratic equations. A quadratic equation is in the form ax²+bx+c = 0. You can find the solutions or roots of any quadratic equation using the formula: -b ± √(b² - 4ac) / (2a).

Let's apply this formula to the quadratic equation, x^2 = -5x - 3. Here, a = 1, b = 5, and c = 3. Substituting these values into the formula, the solutions to this quadratic equation are (-5 - sqrt(13))/2 and (-5 + sqrt(13))/2. However, in the question, there seems to be multiple options. It's essential to note that the correct solutions match the ones derived from our calculations.

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Answer: The largest number was 42

Using the formula for a 95% confidence interval and a Z score of 1.96, Joseph's 95% confidence interval for the percentage of students reporting bullying at their school is roughly 10.1% to 11.9%.

The subject of this problem is statistics, specifically the creation of a 95% confidence interval based on collected data. A confidence interval is a type of estimate computed from the statistics of observed data. This gives a range of values for an unknown parameter (in this case, the number of students experiencing bullying).

In this case, the mean (or average) is 0.15 or 15%. The standard deviation is 0.045 or 4.5%. The sample size, often denoted as 'n', is 186.

Based on the 95% confidence interval, we will use a Z score of 1.96. We can start to calculate our interval using the formula for the confidence interval: sample mean ± (Z * (standard deviation/sqrt(n))).

Using these numbers:

The lower end of the confidence interval is 0.11 - (1.96 * (0.045 / sqrt(186))) = about 0.101 or 10.1%.

The upper end of the confidence interval is 0.11 + (1.96 * (0.045 / sqrt(186))) = about 0.119 or 11.9%.

So, the 95% confidence interval for the percentage of students who reported experiencing bullying one to three times within the most recent month is approximately 10.1% to 11.9%.

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Answer: For every 12 blue pens, she has 6 red pens 12:6

Simplifying this would be: 2:1

Answer:

3 : 1

Step-by-step explanation:

18 : 6

simplified ratio is

3 : 1

Answer:

The maximum price that the dealer will sell is $7471 and the minimum is $5513.

Step-by-step explanation:

Problems of normally distributed samples are solved using 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 problem, we have that:

[tex]\mu = 6492, \sigma = 1025[/tex]

Middle 66%

50 - (66/2)  = 17th percentile

50 + (66/2) = 83rd percentile

17th percentile

X when Z has a pvalue of 0.17. So X when Z = -0.955.

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

[tex]-0.955 = \frac{X - 6492}{1025}[/tex]

[tex]X - 6492 = -0.955*1025[/tex]

[tex]X = 5513[/tex]

83rd percentile

X when Z has a pvalue of 0.83. So X when Z = 0.955.

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

[tex]0.955 = \frac{X - 6492}{1025}[/tex]

[tex]X - 6492 = 0.955*1025[/tex]

[tex]X = 7471[/tex]

The maximum price that the dealer will sell is $7471 and the minimum is $5513.

Final answer:

The interest earned on $9.02 at an 8% interest rate for three years is $2.16.

Explanation:

To calculate the amount of interest earned on a principal of $9.02 at an interest rate of 8% for three years, we would use the formula for simple interest: Interest = Principal  imes Rate  imes Time. Plugging in the values we get:

Interest = $9.02  imes 0.08  imes 3

Interest = $2.166. Therefore, the interest earned on the principal amount of $9.02 invested at an 8% interest rate for three years would be $2.16, after rounding to the nearest cent.

Answer:

18.15% probability of producing a bad product

Step-by-step explanation:

Problems of normally distributed samples are solved using 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 problem, we have that:

[tex]\mu = 3.01, \sigma = 0.02[/tex]

What is the probability of producing a bad product?

Less than 2.97 or more than 3.03.

Less than 2.97

pvalue of Z when X = 2.97. So

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

[tex]Z = \frac{2.97 - 3.01}{0.02}[/tex]

[tex]Z = -2[/tex]

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

More than 3.03

1 subtracted by the pvalue of Z when X = 3.03. So

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

[tex]Z = \frac{3.03 - 3.01}{0.02}[/tex]

[tex]Z = 1[/tex]

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

1 - 0.8413 = 0.1587

Then

0.0228 + 0.1587 = 0.1815

18.15% probability of producing a bad product

Answer:

bcd

Step-by-step explanation:

Answer:

B C D

Step-by-step explanation:

Answer:

(D)

x (x + 2) × (x + 4) = 75

Answer:

D.)x (x + 2) · (x + 4) = 75

Step-by-step explanation:

Well, the easiest way to look at this is by first placing both the 2nd odd integer and the 3rd odd integer into parenthesis finally you simply add the 1st integer to the beginning of the equation. You simply just use the information given and piece it all together into an equation usually written in the same order that the information was given.

Also, to find out the operations in the equations you simply use the keywords given in the problem itself. In this problem, they used the phrase "The product of three consecutive odd integers is 75." since we know that product means to multiply then we also know that we are multiplying all of the integers together to give us our final answer of 75.

Answer:

80

Step-by-step explanation:

So if 50 tablets are made and 2 are defective then it’s 50:2. That means for every 50 tablets are made 2 are defective. And since 50 goes into 2000 40 times, you would multiply 40 x 2 to get 80, the number defective tablets

Answer:

large of a sample size  n = 2645

Step-by-step explanation:

Explanation:-

The population standard deviation 'σ' = 39.9

Given data the estimate is within 2 of the true population mean so given the margin of error = 2

we know that margin of error is determined by

Margin of error = [tex]\frac{z_{\alpha }S.D }{\sqrt{n} }[/tex]

cross multiplication , we get

                    [tex]\sqrt{n} = \frac{2.578 X S.D}{M.E}[/tex]

                    [tex]\sqrt{n} = \frac{2.578 X 39.9}{2}= 51.4311[/tex]

squaring on both sides , we get

                    n = 2645.15

                    n = 2645

Conclusion:-

large of a sample size  n = 2645

Answer:

A) Slope - 1.1889. The Predicted distance the drivers were able to drive increases by 1.1889

Step-by-step explanation:

Answer:

8 ( x + 3 ) , Need more details , hope this was answer

Step-by-step explanation:

Final answer:

The expression 8x + 24 can be factored to 8(x + 3) by taking out the common factor of 8, which is a usual step in simplifying algebraic expressions.

Explanation:

The expression 8x + 24 is a linear algebraic expression with two terms. Typically in algebra, when simplifying expressions or solving equations, we might look for ways to factor or combine like terms. However, in this expression, there's no immediate algebraic simplification other than factoring out a common factor if we wanted to rewrite the expression in a different form.

If we observe that 24 is divisible by 8, we might factor out the number 8 to express the original expression in the form of 8(x + 3). This shows that the expression can be seen as the product of 8 and the quantity (x + 3), which is particularly useful when solving equations or simplifying further expressions that include 8x + 24.

Answer:

B

Step-by-step explanation:

split the triangle in to 5 different shapes

3 of them are rectangles, and 2 are triangles

all of the rectangles are the same size being:

12 by 5  so 12 times 5. then do this 3 times for each rectangle.

Now take the triangles and find the area for those.

which is 1/2 or base times height . so half of 5 multiplied by height (4.3)

being 2.5 times 4.3 giving you 10.75

now take the area of the rectangles and triangles and add them together

60+60+60+10.75+10.75= 201.5 ft2

Answer:

0.233

Step-by-step explanation:

There are a total of 16 marbles.

The probability the first marble is blue is 8/16.

Assuming the marble isn't replaced, the probability the second marble is blue is 7/15.

So the probability of both marbles being blue is 8/16 × 7/15 = 7/30 ≈ 0.233.

The probability of drawing two blue marbles without replacement is 0.233 to the nearest thousandth, calculated by multiplying the individual probabilities of the first and second draws.

The probability of drawing two blue marbles from a bag without replacement involves a two-step calculation because the outcome of the first draw affects the second. Since there are 3 red, 8 blue, and 5 green marbles, the total number of marbles is 16. The probability of drawing a blue marble first is 8/16 or 1/2.

After drawing one blue marble, there would be 7 blue marbles left in a bag of 15 total marbles. The probability of drawing a blue marble on the second draw is then 7/15. To find the combined probability of both events occurring, we multiply the two probabilities: (1/2) × (7/15) = 7/30, which is approximately 0.233 to the nearest thousandth.

Thus, the probability of drawing two blue marbles in a row without replacement is 0.233 to the nearest thousandth.