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Brilliant_brown [7]
3 years ago
5

Jacob is training for a marathon. His plan is to run the same distance for 3 days a week, then increase that distance by the sam

e amount each week of training. During week 6, Jacob runs 14 miles per day, which is 1.5 miles more per day than he ran during week 5. Which equation represents the daily running distance, in miles, as a function of time, t, in weeks?
Mathematics
2 answers:
gregori [183]3 years ago
6 0

Answer:

f(t) = 1.5t + 5

Step-by-step explanation:

Tju [1.3M]3 years ago
5 0
Given:
Week 6 = 14 miles
Week 5 = 1.5 miles less than week 6.

1.5 miles is the common difference.

Week 6 = 14 miles
Week 5 = 12.5 miles
Week 4 = 11 miles
Week 3 = 9.5 miles
Week 2 = 8 miles
Week 1 = 6.5 miles

f(t) = first term + common difference(t-1)
f(t) = 6.5 miles + 1.5 miles (t-1)

f(1) = 6.5 + 1.5(1-1)
f(1) = 6.5 miles

f(2) = 6.5 + 1.5(2-1)
f(2) = 6.5 + 1.5
f(2) = 8 miles
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Answer:

a) The null and alternative hypothesis are:

H_0: \pi=0.53\\\\H_a:\pi

b) If 300 families were sampled, for a significance level of 5%, there is enough evidence to support the claim that a smaller proportion of American families own stocks or stock funds this year than 10 years ago (P-value = 0.001).

 

Step-by-step explanation:

The claim that we want to have evidence to support is that a smaller proportion of American families own stocks or stock funds this year than 10 years ago.

The hypothesis for this test should state:

- For the null hypothesis, that the population proportion is not significantly different from 53%.

H_0:\pi=0.53

- For the alternative hypothesis, that the population proportion is significantly less than 53%.

H_a: \pi

If 300 families are sampled, we can perform a hypothesis test for a proportion.

The claim is that a smaller proportion of American families own stocks or stock funds this year than 10 years ago.

Then, the null and alternative hypothesis are:

H_0: \pi=0.53\\\\H_a:\pi

The significance level is 0.05.

The sample has a size n=300.

The sample proportion is p=0.44.

The standard error of the proportion is:

\sigma_p=\sqrt{\dfrac{\pi(1-\pi)}{n}}=\sqrt{\dfrac{0.53*0.47}{300}}\\\\\\ \sigma_p=\sqrt{0.00083}=0.029

Then, we can calculate the z-statistic as:

z=\dfrac{p-\pi+0.5/n}{\sigma_p}=\dfrac{0.44-0.53+0.5/300}{0.029}=\dfrac{-0.088}{0.029}=-3.065

This test is a left-tailed test, so the P-value for this test is calculated as:

\text{P-value}=P(z

As the P-value (0.001) 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 a smaller proportion of American families own stocks or stock funds this year than 10 years ago.

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Step-by-step explanation:


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