Moose Drool Makes Grass More Appetizing Different species can interact in interesting ways. One type of grass produces the toxin ergovaline at levels about 1.0 part per million in order to keep grazing animals away. However, a recent study27 has found that the saliva from a moose counteracts these toxins and makes the grass more appetizing (for the moose). Scientists estimate that, after treatment with moose drool, mean level of the toxin ergovaline (in ppm) on the grass is 0.183. The standard error for this estimate is 0.016.

Give notation for the quantity being estimated, and define any parameters used.

Give notation for the quantity that gives the best estimate, and give its value.

Give a 95% confidence interval for the quantity being estimated. Interpret the interval in context.

3.68 Bisphenol A in Your Soup Cans Bisphenol A (BPA) is in the lining of most canned goods, and recent studies have shown a positive association between BPA exposure and behavior and health problems. How much does canned soup consumption increase urinary BPA concentration? That was the question addressed in a recent study34 in which consumption of canned soup over five days was associated with a more than 1000% increase in urinary BPA. In the study, 75 participants ate either canned soup or fresh soup for lunch for five days. On the fifth day, urinary BPA levels were measured. After a two-day break, the participants switched groups and repeated the process. The difference in BPA levels between the two treatments was measured for each participant. The study reports that a 95% confidence interval for the difference in means (canned minus fresh) is 19.6 to 25.5 μg/L.

Is this a randomized comparative experiment or a matched pairs experiment? Why might this type of experiment have been used?

What parameter are we estimating?

Interpret the confidence interval in terms of BPA concentrations.

If the study had included 500 participants instead of 75, would you expect the confidence interval to be wider or narrower?

3.70 Effect of Overeating for One Month: Average Long-Term Weight Gain Overeating for just four weeks can increase fat mass and weight over two years later, a Swedish study shows.35 Researchers recruited 18 healthy and normal-weight people with an average age of 26. For a four-week period, participants increased calorie intake by 70% (mostly by eating fast food) and limited daily activity to a maximum of 5000 steps per day (considered sedentary). Not surprisingly, weight and body fat of the participants went up significantly during the study and then decreased after the study ended. Participants are believed to have returned to the diet and lifestyle they had before the experiment. However, two and a half years after the experiment, the mean weight gain for participants was 6.8 lbs with a standard error of 1.2 lbs. A control group that did not binge had no change in weight.

What is the relevant parameter?

How could we find the actual exact value of the parameter?

Give a 95% confidence interval for the parameter and interpret it.

Give the margin of error and interpret it.

The question relates to a two-sample t-test in statistics, which compares the means of two processes. It involves calculating a t-score using sample data, and comparing this score to a critical value to determine if there is a significant difference between the two processes.

This question pertains to the field of statistics within mathematics. Specifically, it involves the use of a two-sample t-test to compare the means of two different processes. The two-sample t-test is used when the population standard deviations are unknown but assumed to be equal, which is the case here.

The process involves computing a t-score using the observed data (including sample mean, standard deviation, and sample size) and then comparing this score to a critical value from the t-distribution. If the observed t-score exceeds the critical value, there is evidence to suggest that there is a significant difference between the two processes.

In this case, you would calculate the t-score for Processes A and B using their respective sample means, standard deviations, and sample sizes. If the observed t-score is greater than the critical t-value at the chosen significance level (typically 0.05 or 0.01), we reject the null hypothesis that there is no difference between the two processes.

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Diego’s travel distance can be determined by first subtracting the pickup fee from the total fare and then dividing this result by the cost per mile. In this case, Diego traveled a total of 11 miles.

To calculate Diego’s travel distance, begin by subtracting the pickup fee from the total fare. The pickup fee is $2.75 and the total fare is $19.25, so this calculation gives us $19.25 - $2.75 = $16.50. Next, divide this result by the cost per mile to determine the total distance traveled. As City cabs charge $1.50 per mile, this calculation is $16.50 ÷ $1.50 = 11. So, Diego traveled 11 miles in the cab.

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Diego traveled 11 miles in the city cab, as calculated by subtracting the fixed pickup fee from the total fare and then dividing by the cost per mile.

City cabs charges a $2.75 pickup fee and $1.50 per mile traveled. If Diego's fare for a cross-town cab ride is $19.25, the question asks us to calculate how far he traveled in the cab. To solve this, we need to use the equation of the total fare which is:

Total fare = Pickup fee + (Cost per mile × Number of miles)

Let 'x' be the number of miles Diego traveled. Using the above equation and substituting the given values, we have:

$19.25 = $2.75 + ($1.50 × x)

To find 'x', we will subtract the pickup fee from the total fare and then divide the result by the cost per mile:

$19.25 - $2.75 = $1.50 × x

$16.50 = $1.50 × x

x = $16.50 / $1.50

x = 11

Therefore, Diego traveled 11 miles in the cab.

Answer:

Combine the like terms

Step-by-step explanation:

2 + 7 = 2x + 5 - 43

The first step is to combine the like terms

9 = 2x - 38

Answer:

The diameter is 3 inches

Step-by-step explanation:

If you are calculating a circle, one of the main rules you should know is that the diameter is double the radius. In this case the radius is 1.5 inches long. If you need the diameter, you need to double that figure; in this case the answer is 3 inches

Answer:

3 inches

Step-by-step explanation:

diameter is twice the length of the radius

1.5x2=3

Answer: D. 7 or 12

Step-by-step explanation: on edgenuity 2020 :))

Answer:

25 posts

Step-by-step explanation:

So the number of fence post would be the total length of the log divided by the length of each post. As the log is 16m and is corrected to the nearest metre, it could possibly be 16.499m. As for the post that is 70 cm long and corrected to the nearest 10cm, it may as well be 65 cm (or 0.65m) each post

So the max number of fence point once can possibly cut from the log would be

16.499 / 0.65 = 25 posts

Answer:

18.59% probability that EXACTLY 10 will show that the above three food items were ordered

Step-by-step explanation:

For each customer, there are only two possible outcomes. Either they order the above food items, or they do not. The probability of a customer ordering these items is independent of other customers. So we use the binomial probability distribution to solve this question.

Binomial probability distribution

The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.

[tex]P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}[/tex]

In which [tex]C_{n,x}[/tex] is the number of different combinations of x objects from a set of n elements, given by the following formula.

[tex]C_{n,x} = \frac{n!}{x!(n-x)!}[/tex]

And p is the probability of X happening.

Sixty percent of the customers of a fast food chain order the Whopper, french fries and a drink.

This means that [tex]p = 0.6[/tex]

If a random sample of 15 cash register receipts is selected, what is the probability that EXACTLY 10 will show that the above three food items were ordered

This is P(X = 10) when n = 15. So

[tex]P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}[/tex]

[tex]P(X = 10) = C_{15,10}.(0.6)^{10}.(0.4)^{5} = 0.1859[/tex]

18.59% probability that EXACTLY 10 will show that the above three food items were ordered

Answer:

a) The standard error would be of 8.58 pounds.

b) The margin of error is 14.11 pounds.

c) The 90% confidence interval for the population mean is between 232.89 pounds and 261.11 pounds

Step-by-step explanation:

a.What is the standard error?

The standard error is

[tex]s = \frac{\sigma}{\sqrt{n}}[/tex]

In which [tex]\sigma[/tex] is the standard deviation of the population and n is the size of the sample. So

[tex]s = \frac{47}{\sqrt{30}} = 8.58[/tex]

The standard error would be of 8.58 pounds.

b.What is the margin of error at 90% confidence?

We have that to find our [tex]\alpha[/tex] level, that is the subtraction of 1 by the confidence interval divided by 2. So:

[tex]\alpha = \frac{1-0.9}{2} = 0.05[/tex]

Now, we have to find z in the Ztable as such z has a pvalue of [tex]1-\alpha[/tex].

So it is z with a pvalue of [tex]1-0.05 = 0.95[/tex], so [tex]z = 1.645[/tex]

Now, find the margin of error M as such

[tex]M = z*s = 1.645*8.58 = 14.11[/tex]

The margin of error is 14.11 pounds.

c. Using my sample of 30, what would be the 90% confidence interval for the population mean?

Lower bound: Sample mean subtracted by the margin of error.

247 - 14.11 = 232.89 pounds

Upper bound

247 + 14.11 = 261.11 pounds

The 90% confidence interval for the population mean is between 232.89 pounds and 261.11 pounds

Answer:

a) The standard error would be of 8.58 pounds.

b) The margin of error is 14.11 pounds.

c) The 90% confidence interval for the population mean is between 232.89 pounds and 261.11 pounds

Step-by-step explanation:

Answer:

Yes, there is  enough evidence to support the claim that ionizing radiation is beneficial in terms of marketability.

Step-by-step explanation:

This is a hypothesis test for the difference between proportions.

The claim is that ionizing radiation is beneficial in terms of marketability.

Then, the null and alternative hypothesis are:

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

Being π1: the true proportion of treated bulbs that can be comercialized after 240 days, and π2: the true proportion of untreated bulbs that can be comercialized after 240 days.

The significance level is 0.05.

The sample 1, of size n1=180 has a proportion of p1=0.85.

[tex]p_1=X_1/n_1=153/180=0.85[/tex]

The sample 2, of size n2=180 has a proportion of p2=0.65.

[tex]p_2=X_2/n_2=117/180=0.65[/tex]

The difference between proportions is (p1-p2)=0.2.

[tex]p_d=p_1-p_2=0.85-0.65=0.2[/tex]

The pooled proportion, needed to calculate the standard error, is:

[tex]p=\dfrac{X_1+X_2}{n_1+n_2}=\dfrac{153+117}{180+180}=\dfrac{270}{360}=0.75[/tex]

The estimated standard error of the difference between means is computed using the formula:

[tex]s_{p1-p2}=\sqrt{\dfrac{p(1-p)}{n_1}+\dfrac{p(1-p)}{n_2}}=\sqrt{\dfrac{0.75*0.25}{180}+\dfrac{0.75*0.25}{180}}\\\\\\s_{M_d}=\sqrt{0.001+0.001}=\sqrt{0.002}=0.0456[/tex]

Then, we can calculate the z-statistic as:

[tex]z=\dfrac{p_d-(\pi_1-\pi_2)}{s_{p1-p2}}=\dfrac{0.2-0}{0.0456}=\dfrac{0.2}{0.0456}=4.382[/tex]

This test is a right-tailed test, so the P-value for this test is calculated as (using a z-table):

[tex]P-value=P(t>4.382)=0.000008[/tex]

As the P-value (0.000008) is smaller than the significance level (0.05), the effect is significant.

The null hypothesis is rejected.

There is  enough evidence to support the claim that ionizing radiation is beneficial in terms of marketability.

Final answer:

The observed marketable rate of irradiated garlic bulbs suggests that ionizing radiation is beneficial to their marketability compared to untreated bulbs, and this could be statistically tested for significance.

Explanation:

The student's data indicates that irradiated garlic bulbs have a significantly higher rate of remaining marketable (85%) after 240 days compared to unirradiated bulbs (65%). Using a significance level of α = 0.05, we can infer a positive effect of ionizing radiation on the marketability of garlic bulbs. To statistically confirm this observation, one could perform a hypothesis test (such as a chi-squared test for independence) to determine if the difference in marketability between the treated and untreated groups is significant.

Answer:

[tex]t=\frac{7.917-9.5}{\frac{1.501}{\sqrt{6}}}=-2.58[/tex]    

[tex]p_v =P(t_{5}<-2.58)=0.03[/tex]

If we compare the p value with a significance level for example [tex]\alpha=0.05[/tex] we see that [tex]p_v < \alpha[/tex] so we can conclude that we can reject the null hypothesis, and there is enough evidence to conclude that the true mean is significantly lower than 9.5% at 0.05 of signficance

Step-by-step explanation:

Data given and notation    

Data: 6.6% 9.1% 7.0% 6.3% 8.5% 10.0%

We can calculate the mean and the sample deviation with the following formulas:

[tex] \bar X = \frac{\sum_{i=1}^n X_i}{n}[/tex]

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

[tex]\bar X=7.917[/tex] represent the sample mean

[tex]s=1.501[/tex] represent the sample standard deviation

[tex]n=6[/tex] sample size    

[tex]\mu_o =9.5[/tex] represent the value that we want to test  

[tex]\alpha[/tex] represent the significance level for the hypothesis test.  

t would represent the statistic (variable of interest)    

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

State the null and alternative hypotheses.    

We need to conduct a hypothesis in order to determine if the true mean os greater or not than 9.5%, the system of hypothesis would be:    

Null hypothesis:[tex]\mu \geq 9.5[/tex]    

Alternative hypothesis:[tex]\mu < 9.5[/tex]    

We don't know the population deviation, so for this case we can use the t test to compare the actual mean to the reference value, and the statistic is given by:    

[tex]t=\frac{\bar X-\mu_o}{\frac{s}{\sqrt{n}}}[/tex] (1)    

t-test: "Is used to compare group means. Is one of the most common tests and is used to determine if the mean is (higher, less or not equal) to an specified value".

Calculate the statistic    

We can replace in formula (1) the info given like this:    

[tex]t=\frac{7.917-9.5}{\frac{1.501}{\sqrt{6}}}=-2.58[/tex]    

Calculate the P-value    

The degrees of freedom are given by:

[tex] df = n-1 = 6-1=5[/tex]

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

[tex]p_v =P(t_{5}<-2.58)=0.03[/tex]

In Excel we can use the following formula to find the p value "=T.DIST(-2.58,5,TRUE)"  

Conclusion    

If we compare the p value with a significance level for example [tex]\alpha=0.05[/tex] we see that [tex]p_v < \alpha[/tex] so we can conclude that we can reject the null hypothesis, and there is enough evidence to conclude that the true mean is significantly lower than 9.5% at 0.05 of signficance

The test statistic of the sampling will be -2.58.

The following can be deduced from the information:

Mean = 7.917

Degree of freedom = 6 - 1 = 5

P value = 0.975 > 0.05

The test statistic will be:

= (7.917 - 9.5) / (1.501 / ✓56)

= -2.58

In conclusion, the test statistic is -2.58.

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Answer:

nothing

Step-by-step explanation:

nothing

Answer:

350(1.137)^20=4563.28232

Answer:

Estimate of the population proportion [tex]\mathbf{\widehat{(P)}}[/tex] = 0.147

Step-by-step explanation:

Given -

Wiley Publications has determined that out of a sample of 7,831 of its publications for 2012, 1,157 of them had been pirated online in some form.

Let x be the no of publication had been pirated online in some form.

x = 1157

n = 7831

Population proportion [tex]\boldsymbol{\widehat{P} = \frac{x}{n}}[/tex]

                                           =  [tex]\frac{1157}{7831}[/tex]

                                         =  0.147

Answer:

(a) I attached a photo with the diagram.

(b) [tex]f(x) = \big( \frac{1}{2} \big)^{x-1}[/tex]

(c) 1/4

(d) 4

(e) [tex]k^2/2[/tex]

Step-by-step explanation:

(a) I attached a photo with the diagram.

(b) The easiest way to think about this part is in terms of combinatorics. Think about it like this.

To begin with, look at the three each level of the three represents a possible outcome of throwing the coin n-times. If you throw the coin 3 times at the end in total there are 8 possible outcomes. But The favorable outcomes are just 2.

 1  - Your first outcome is HEADS and all the others are different except the last one.

 2  - Your first outcome is TAILS and all the others are different except the last one.

Therefore the probability of the event is

[tex]f(x) = P(X=x) = \frac{2}{2^x} = \frac{1}{2^{x-1}} = \big( \frac{1}{2} \big)^{x-1}[/tex]

(c)

P(X = 0) = 0 because it is not possible to have two consecutive tails or heads.

[tex]E(X > 4) = 1 - P(X \leq 3) = 1 - ( P(X = 0 ) + P(X = 1) + P(X = 2) + P(X = 3))\\= 1 - ( \frac{1}{2} + \frac{1}{4} ) = \frac{1}{4}[/tex]

(d)

Remember that this is a geometric distribution therefore

[tex]E[X] = p/(1-p)[/tex], in this case  [tex]p = 1/2[/tex] so [tex]E[X] = 1[/tex] and

[tex]E[X+1]^2 = ( E[X] +1 )^2 = (1+1)^2 = 2^2 = 4[/tex]

Also

(e)

This is a geometric distribution so its variance is

[tex]Var(X) = \frac{1-p}{p^2} = 1/2 / 1/4 = 1/2[/tex]

And using properties of variance

[tex]Var(kX - k ) = Var(kX) = k^2 var(X) = k^2 /2[/tex]

To find the required answers, we create a tree diagram to visualize the possibilities of flipping a fair coin. Then, we determine the probability mass function (pmf) of X, finding the probabilities associated with each outcome. We find that P(X=0) is not possible and P(X>4) is 0. We also calculate E((X+1)^2) and Var(kX-k) using the formulas for expected value and variance of a discrete random variable.

To answer the question, we first need to understand the possibilities when flipping a coin. Let H represent a heads and T represent a tails. The possibilities are: HT, TH, and HH. Now, let's create a tree diagram to visualize the possibilities:

(b) To find the probability mass function (pmf) of X, we need to determine the probability of each outcome. Since the coin is fair, each outcome has a probability of 1/2. Therefore, the pmf of X is: P(X=1) = 1/2, P(X=2) = 1/4, P(X=3) = 1/4.

(c) (i) P(X=0) is not possible because we need to observe tails-heads in consecutive flips. (ii) P(X>4) is the probability of observing tails-heads after at least 4 flips, which is 0 since tails-heads can occur in the 2nd or 3rd flip.

(d) To find E((X+1)^2), we need to multiply each possible outcome by its corresponding probability, square it, and then sum them up. E((X+1)^2) = (0+1)^2 * P(X=1) + (1+1)^2 * P(X=2) + (2+1)^2 * P(X=3).

(e) Var(kX-k) = k^2 * Var(X), where Var(X) is the variance of X. Since X is a discrete random variable, Var(X) = E(X^2) - (E(X))^2.

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Answer:

D

Step-by-step explanation:

200 men and 2,000 women

i dont know how but that was just the answer

The sampling distribution of ā-Ă will be approximately normal when both populations satisfy the conditions for np > 5 and nq > 5. The sample sizes must ensure these inequalities are met using the proportions 0.08 for men and 0.005 for women.

The sampling distribution of ā - Ă will be approximately normal when the sample sizes are large enough to satisfy the condition np > 5 and nq > 5 for both populations. Given that in the population of men, 8 percent carry the genetic trait (p1 = 0.08), and in the population of women, 0.5 percent carry the trait (p2 = 0.005), we need to find appropriate sample sizes for each population.

For the men's population:
n1p1 > 5 and n1(1 - p1) > 5.

For the women's population:
n2p2 > 5 and n2(1 - p2) > 5.

The sample sizes should be selected in a way that these inequalities are met for both populations to ensure that the sampling distribution of ā-Ă is approximately normal.

Answer:

30 hours

Step-by-step explanation:

We can use ratios to solve

5 hours        x hours

-------------- = -------------

3 walls          18 walls

Using cross products

5*18 = 3x

Divide each side by 3

5*18/3 = 3x/3

30 =x

Answer:It will take Harold 30 hours to paint all 18 of the walls

Step-by-step explanation:Your multiplying the amount of walls he is painting by 6 so you do the same to the amount of hours he is painting

Answer:

[tex]28-2.064\frac{10}{\sqrt{25}}=23.872[/tex]    

[tex]28+2.064\frac{10}{\sqrt{25}}=32.128[/tex]    

So on this case the 95% confidence interval would be given by (23.9;32.1)  

Step-by-step explanation:

Previous concepts

A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".

The margin of error is the range of values below and above the sample statistic in a confidence interval.

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

[tex]\bar X=28[/tex] represent the sample mean

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

s=10 represent the sample standard deviation

n=25 represent the sample size  

Solution to the problem

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

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

In order to calculate the critical value [tex]t_{\alpha/2}[/tex] we need to find first the degrees of freedom, given by:

[tex]df=n-1=25-1=24[/tex]

Since the Confidence is 0.95 or 95%, the value of [tex]\alpha=0.05[/tex] and [tex]\alpha/2 =0.025[/tex], and we can use excel, a calculator or a table to find the critical value. The excel command would be: "=-T.INV(0.025,24)".And we see that [tex]t_{\alpha/2}=2.064[/tex]

Now we have everything in order to replace into formula (1):

[tex]28-2.064\frac{10}{\sqrt{25}}=23.872[/tex]    

[tex]28+2.064\frac{10}{\sqrt{25}}=32.128[/tex]    

So on this case the 95% confidence interval would be given by (23.9;32.1)    

The 95% confidence interval for the average age of the boutique's customers is from 24.1 to 31.9 years, calculated using the sample mean of 28 years, a standard deviation of 10 years, and a sample size of 25.

To calculate a 95% confidence interval for the average age of all customers in the boutique, we will use the sample mean, standard deviation, and the size of the sample along with the z-score corresponding to a 95% confidence level.

The formula for a confidence interval when the population standard deviation is known is:

Confidence interval = {x} (Z  {Σ}/√{n}})

In this case, we have:

Sample mean ({x}): 28 years

Standard deviation (Σ): 10 years

Sample size (n): 25

Z-score for 95% confidence: 1.96 (from z-tables)

First, we calculate the margin of error:

The margin of error = Z{Σ}/{√{n}} = 1.96  {10}/{√{25}} = 1.96 × 2 = 3.92

Then, the confidence interval is:

Lower limit = {x} - Margin of error = 28 - 3.92 = 24.08

Upper limit = {x} + Margin of error = 28 + 3.92 = 31.92

Therefore, the 95% confidence interval for the average age of the boutique's customers is from 24.1 to 31.9 years.

Use log definition: if logₐ(b) = c then b = a^c

log₃(x) = 6 → x = 3⁶

x = 3⁶ → x = 726

Therefore, x = 726

Best of Luck!

Answer:

Step-by-step explanation:

CB is the radius. It is equal to BD. So, the diameter CD is ...

  6 inches + 6 inches = 12 inches

The diameter is always twice the length of the radius.

The diameter of this cone is 12 inches.

Answer:

[tex]4600-1.646\frac{800}{\sqrt{1800}}=4568.96[/tex]    

[tex]4600+1.646\frac{800}{\sqrt{1800}}=4631.04[/tex]    

We are confident at 90% that the true mean for the amount spent on medicines is between (4568.96 and 4631.04)

Step-by-step explanation:

Information given

[tex]\bar X=4600[/tex] represent the sample mean for the amount spent on medicines

[tex]\mu[/tex] population mean

s=800 represent the sample standard deviation

n=1800 represent the sample size  

Solution

The confidence interval for the true population mean is given by:

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

We can calculate the degrees of freedom with:

[tex]df=n-1=1800-1=1799[/tex]

We know that the Confidence level is 0.90 or 90%, the value of significance is [tex]\alpha=0.1[/tex] and [tex]\alpha/2 =0.05[/tex], and we can use excel, a calculator or a table to find the critical value. The excel command would be: "=-T.INV(0.05,1799)".And we see that [tex]t_{\alpha/2}=1.646[/tex]

Replcing in the formula for the confidence interval we got:

[tex]4600-1.646\frac{800}{\sqrt{1800}}=4568.96[/tex]    

[tex]4600+1.646\frac{800}{\sqrt{1800}}=4631.04[/tex]    

We are confident at 90% that the true mean for the amount spent on medicines is between (4568.96 and 4631.04)

To compare the number of artists with hit songs to the total number of artists signed, write a ratio using the two numbers. The ratio of artists with hit songs (10) to total artists signed (12) simplifies to 5:6 after dividing by the greatest common factor.

The student has asked to write a ratio comparing the number of artists with hit songs to the total number of artists signed by a music company in 2002. To do this, we take the number of artists with hit songs and place it in the numerator (top part) of the ratio and the total number of artists in the denominator (bottom part).

To write the ratio in its simplest form, we divide the numerator and the denominator by their greatest common factor if necessary. In this case, the ratio is already in the simplest form.

Step-by-Step Solution:

Number of artists with hit songs: 10

Total number of artists signed: 12

Write the ratio as 10:12

Simplify the ratio by dividing both numbers by 2, the greatest common factor, to get 5:6

So, the simplified ratio of the number of artists with hit songs to the total number of artists signed is 5:6.

Answer: inverse operation

Step-by-step explanation:

here you go

Answer:

  yes, brother can go

Step-by-step explanation:

Apparently, you're not to think to deeply about this function. Rather, you are to take the question at face value. It is asking if the value of T(3) is more than 58.

Evaluation of polynomials is facilitated by writing them in "Horner form."

  T(x) = ((x -2)x +1)x^2 +27

  T(3) = ((3 -2)3 +1)9 +27 = (3 +1)9 +27 = 36 +27

  T(3) = 63

The coldest temperature is supposed to be 63 degrees, which is above 58 degrees. Baby brother can come along.

Answer:

yes, the little brother can go

Step-by-step explanation:

the lowest will be 63 degrees so the baby can go

Answer:

B is the correct answer.

Step-by-step explanation:

15 times 5 plus 450

= 525

25 times 5 plus 400

= 525

a) Little book LTD earning per share is $1.118 per share.  

Explanation:

To calculate earning per share we will use following formula:[tex]\frac{NET INCOME}{WEIGHTED AVERAGE SHARE OUTSTANDING}[/tex]

Now to find net income we will take help of  asset turnover ratio :[tex]\frac{NET SALES}{TOTAL ASSET}[/tex]

NOTE :  LET x BE THE NET SALES DURING THE YEAR.

Asset turnover ratio = [tex]\frac{x}{860000}[/tex]

1.5 × $860000 = x

x (net sales) = $1290000

Outstanding shares = 75000 shares

So Net Income  = $1290000×.065

                         = $83850

Now Earning per share = [tex]\frac{83850}{75000}[/tex]

 Earning per share = $1.118

b)  Market to Book Ratio will be 1.2 for Little Book LTD.

Explanation:

Market to Book Ratio =[tex]\frac{MARKET CAPITALIZATION}{TOTAL BOOK VALUE}[/tex]

Market Capitalization = $ 75000× $ 12

                                   = $900000

So, Market To Book Ratio =[tex]\frac{900000}{750000}[/tex] =  1.2

    So , Market To Book Ratio is 1.2  for little book ltd.