Ivanna drove 696 miles in 12 hours. At the same rate, how many miles would she drive in 7 hours?

Answers

Answer 1

Answer:

Answer:

406

Step-by-step explanation:

We need to find the unit rate or how many miles can they drive in 1 hour. So we do 696/12 which is 58. So we have 58 miles in 1 hour. Now we multiply the number of desired hours, 7 and multiply it by 696. Which is 406

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The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting the number of bids an item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Price in Dollars 25 33 34 45 48Number of Bids 2 3 4 5 7 Step 1 of 6: Find the estimated slope. Round your answer to three decimal places.Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places.Step 3 of 6: Find the estimated value of y when x = 34. Round your answer to three decimal places.Step 4 of 6: Determine the value of the dependent variable yˆ at x = 0.Step 5 of 6: Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the value of the independent variable is increased by one unit, then find the change in the dependent variable yˆ.Step 6 of 6: Find the value of the coefficient of determination.
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Mary sells to her father, robert, her shares in a corp for $55,000. the shares cost mary $80,000. how much loss may mary claim from the sale

Answers

Mary Purchase shares = $80,000
Mary Sells shares = $55,000

Loss she can claim for = $80,000 - $55,000
= $ 25,000

Solve the following equation for a: -g + 3/4a = y

Answers

9514 1404 393

Answer:

a = (4/3)(y+g)

Step-by-step explanation:

Isolate 'a' term, then multiply by the reciprocal of its coefficient.

$-g+(3)/(4)a=y\qquad\text{given}\n\n(3)/(4)a=y+g\qquad\text{add $g$}\n\n\boxed{a=(4(y+g))/(3)}\qquad\text{multiply by $4/3$}$

During the soccer season, Cathy made 27 of the 54 goals she attempted. Karla made 18 of the 45 goals she attempted. Patty made 34% of the goals she attempted. List the athletes in order of their goal-scoring percentage from least to greatest.

Answers

Answer:

Patty, Karla, Cathy

Step-by-step explanation:

The scoring percentage of goals attempted can be computed by dividinggoals made by those attempted, then multiplying the result by 100%.

Cathy's rate is ...

27/54 × 100% = 50%

Karla's rate is ...

18/45 × 100% = 40%

Patty's rate is ...

given as 34%

By least to greatest scoring rate, the athletes are ...

Patty (34%), Karla (40%), Cathy (50%)

If each of the numbers in the following data set were multiplied by 22, what would be the new median of the data set? 14, 20, 18, 58, 71, 36

Answers

The new median of the data set will be 616.

What is Multiplication?

To multiply means to add a number to itself a particular number of times. Multiplication can be viewed as a process of repeated addition.

Given that;

The data set is,

⇒ 14, 20, 18, 58, 71, 36

Now,

Since, The data set is,

⇒ 14, 20, 18, 58, 71, 36

Multiply by 22 in each number , we get;

⇒ 14 × 22, 20 × 22, 18 × 22, 58 × 22, 71 × 22, 36 × 22

⇒ 308, 440, 396, 1276, 1562, 792

Arrange the number is ascending order we get;

⇒ 308, 396, 440, 792, 1276, 1562

So, The median of data set = (440 + 792) / 2

= 1232/2

= 616

Thus, The new median of data set = 616

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Answer:

If each of the numbers in the following data set were multiplied by 31, what would be the median of the data set?

28, 58, 20, 14, 18, 71, 36

A. 558

B. 1116

C. 434

D. 868

answer

D.868

Ten years ago 53% of American families owned stocks or stock funds. Sample data collected by the Investment Company Institute indicate that the percentage is now 46% (the Wall Street Journal, October 5, 2012)a. Develop appropriate hypotheses such that rejection of H0 will support the conclusion that a smaller proportion of American families own stocks or stock funds in 2012 than 10 years ago.
b. Assume the Investment Company Institute sampled 300 American families to estimate that the percent owning stocks or stock funds was 46% in 2012. What is the p-value for your hypothesis test?
c. At α = .01, what is your conclusion?

Answers

Using the z-distribution, as we are working with a proportion, it is found that:

a) $H_0: p = 0.53$ , $H_1: p < 0.53$

b) The p-value is of 0.0075.

c) Since the p-value of the test is of 0.0075 < 0.01 for the left-tailed test, it is found that there is enough evidence to reject the null hypothesis and conclude that a smaller proportion of American families own stocks or stock funds in 2012 than 10 years ago.

What are the hypothesis tested?

At the null hypothesis, it is tested if the proportion is still of 53%, that is:

$H_0: p = 0.53$

At the alternative hypothesis, it is tested if the proportion is now smaller, that is:

$H_1: p < 0.53$

Item a:

The hypothesis are:

$H_0: p = 0.53$

$H_1: p < 0.53$

Item b:

The test statistic is given by:

$z = \frac{\overline{p} - p}{\sqrt{(p(1-p))/(n)}}$

In which:

$\overline{p}$ is the sample proportion.

p is the proportion tested at the null hypothesis.

n is the sample size.

In this problem, the parameters are:

$\overline{p} = 0.46, p = 0.53, n = 300$ .

Hence, the value of the test statistic is given by:

$z = \frac{\overline{p} - p}{\sqrt{(p(1-p))/(n)}}$

$z = \frac{0.46 - 0.53}{\sqrt{(0.53(0.47))/(300)}}$

$z = -2.43$

Using a z-distribution calculator, considering a left-tailed test, as we are testing if the proportion is less than a value, with z = -2.43, it is found that the p-value is of 0.0075.

Item c:

Since the p-value of the test is of 0.0075 < 0.01 for the left-tailed test, it is found that there is enough evidence to reject the null hypothesis and conclude that a smaller proportion of American families own stocks or stock funds in 2012 than 10 years ago.

More can be learned about the z-distribution at brainly.com/question/26454209

Answer:

a) Null hypothesis: $p\geq 0.53$

Alternative hypothesis: $p < 0.53$

b) $z=\frac{0.46 -0.53}{\sqrt{(0.53(1-0.53))/(300)}}=-2.429$

$p_v =P(Z<-2.429)=0.0076$

c) So the p value obtained was a very low value and using the significance level given $\alpha=0.01$ we have $p_v<\alpha$ so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 1% of significance the proportion of American families owning stocks or stock funds is significantly less than 0.53 .

Step-by-step explanation:

Data given and notation

n=300 represent the random sample taken

$\hat p=0.46$ estimated proportion of American families owning stocks or stock funds

$p_o=0.53$ is the value that we want to test

$\alpha=0.01$ represent the significance level

Confidence=99% or 0.99

z would represent the statistic (variable of interest)

$p_v$ represent the p value (variable of interest)

Concepts and formulas to use

Part a

We need to conduct a hypothesis in order to test the claim that proportion is less than 0.53 or 53%.:

Null hypothesis: $p\geq 0.53$

Alternative hypothesis: $p < 0.53$

Part b

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

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

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

Calculate the statistic

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

$z=\frac{0.46 -0.53}{\sqrt{(0.53(1-0.53))/(300)}}=-2.429$

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 significance level provided $\alpha=0.01$ . The next step would be calculate the p value for this test.

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

$p_v =P(Z<-2.429)=0.0076$

Part c

So the p value obtained was a very low value and using the significance level given $\alpha=0.01$ we have $p_v<\alpha$ so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 1% of significance the proportion of American families owning stocks or stock funds is significantly less than 0.53 .

A survey of 300 parks showed the following. 15 had only camping. 20 had only hiking trails. 35 had only picnicking. 185 had camping. 140 had camping and hiking trails. 125 had camping and picnicking. 210 had hiking trails. Determine the number of parks that:

a. Had at least one of these features.
b. Had all three features.
c. Did not have any of these features.
d. Had exactly two of these features.

Answers

Answer:

A. 290 parks dad at least one of these features.

b. 95 parks had all three features.

c. 10 parks did not have any of these features.

d. 125 parks had exactly two of these features.

Step-by-step explanation:

This will be solved using set notation according to the venn diagram attached.

Let n(U) be the total number of parks surveyed

n(C) be those that had camping = 185

n(H) be those that had hiking trails = 210

n(C∩H) be those that had camping and hiking trails = 140

n(C∩P) be those that had camping and picnicking = 125

n(C∩P'∩H') be those that had only camping = 15

n(C'∩P'∩H) be those that had only hiking trails = 20

n(C'∩P∩H') be those that had only picnicking = 35

Find the calculation in the attached file

Final answer:

The number of parks that had at least one of the listed features was 135.

The number of parks that had all three features was 20.

The number of parks that did not have any of these features was 165.

Explanation:

To determine the number of parks that had at least one of the listed features, we can add up the numbers of parks that had only camping, only hiking trails, and only picnicking. Then we subtract the parks that had two or three of these features, as they were already counted in the previous step. Doing this calculation, we get:

Parks with at least one feature: 15 + 20 + 35 + (185 - 140 - 125) + (140 - 125) + (210 - 140 - 125) = 135

To find the number of parks that had all three features, we need to subtract the parks that had only camping, only hiking trails, only picnicking, or none of these features from the total number of parks (300). Doing this calculation, we get:

Parks with all three features: 300 - 15 - 20 - 35 - (185 - 140 - 125) - (140 - 125) - (210 - 140 - 125) - (300 - 135) = 20

To determine the number of parks that did not have any of these features, we subtract the parks with at least one feature from the total number of parks (300). Doing this calculation, we get:

Parks with no features: 300 - 135 = 165

To calculate the number of parks that had exactly two features, we add the intersections of each pair of features and subtract the parks that had all three features. Doing this calculation, we get:

Parks with exactly two features: (185 - 140 - 125) + (140 - 125) + (210 - 140 - 125) - (300 - 20) = 60

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