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Rama09 [41]
3 years ago
7

A golf ball is hit off a tee at the edge of a cliff. Its x and y coordinates as functions of time are given by x = 18.1t and y =

4.20t − 4.90t2, where x and y are in meters and t is in seconds. (a) Write a vector expression for the ball's position as a function of time, using the unit vectors î and ĵ. (Give the answer in terms of t.)
Mathematics
1 answer:
Kitty [74]3 years ago
8 0

Answer:

The vector for the ball’s position is \vec{r} = (18.1t)\hat{i} + (4.20t - 4.90t^2)\hat{j} \:m

Step-by-step explanation:

The position vector for a particle moving in the <em>x-y</em> plane can be written

\vec{r} = x\hat{i} + y\hat{j}

where x, y, and \vec{r} change with time as the particle moves while the unit vectors \hat{i} and \hat{j} remain constant.

We know that the x and y coordinates as functions of time are given by x = 18.1t and y = 4.20t - 4.90t^2, where <em>x </em>and<em> y</em> are in meters and <em>t</em> is in seconds.

Therefore, the vector for the ball’s position is \vec{r} = (18.1t)\hat{i} + (4.20t - 4.90t^2)\hat{j} \:m

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Step-by-step explanation:

So, c is the same as c^ 1 ... therefore

c^5 x c

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So c^5 x c^1

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What sample size is needed to give a margin of error within in estimating a population mean with 95% confidence, assuming a prev
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Answer:

n = (\frac{1.96\sqrt{\pi(1-\pi)}}{M})^2

The sample size needed is n(if a decimal number, round up to the next integer), considering the estimate of the proportion \pi(if no previous estimate use 0.5) and M is the desired margin of error.

Step-by-step explanation:

In a sample with a number n of people surveyed with a probability of a success of \pi, and a confidence level of 1-\alpha, we have the following confidence interval of proportions.

\pi \pm z\sqrt{\frac{\pi(1-\pi)}{n}}

In which

z is the z-score that has a p-value of 1 - \frac{\alpha}{2}.

The margin of error is of:

M = z\sqrt{\frac{\pi(1-\pi)}{n}}

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So \alpha = 0.05, z is the value of Z that has a p-value of 1 - \frac{0.05}{2} = 0.975, so Z = 1.96.

Needed sample size:

The needed sample size is n. We have that:

M = z\sqrt{\frac{\pi(1-\pi)}{n}}

M = 1.96\sqrt{\frac{\pi(1-\pi)}{n}}

\sqrt{n}M = 1.96\sqrt{\pi(1-\pi)}

\sqrt{n} = \frac{1.96\sqrt{\pi(1-\pi)}}{M}

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