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Ostrovityanka [42]
3 years ago
6

Arianna kicks a soccer ball off the ground and into the air with an initial velocity of 42 feet per second. Assume the starting

height of the ball is 0 feet. Approximately how long does it take until the soccer ball hits the ground again?
1.3 secs
2.6 secs
16.0 secs
27.6 secs
Mathematics
2 answers:
beks73 [17]3 years ago
7 0
A=g

v=⌠g dt

v=gt+C, where C=v initial

v=gt+vi

h=⌠v dt

h=gt^2/2+vit+C, where C=h initial

h=gt^2/2+vit+hi

We are told that vi=42 ft/s, hi=0, and we know g≈-32 ft/s^2 so

h(t)=-16t^2+42t

The ball will hit the ground when h=0 so

-16t^2+42t=0

-2t(8t-21)=0, since t>0

8t-21=0

8t=21

t=21/8

t=2.625 sec

t≈2.6 sec (to nearest tenth of a second)
Mashcka [7]3 years ago
7 0

Answer:

Step-by-step explanation:

2.6 seconds is the correct answer for this problem

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PtichkaEL [24]
Here are a few doubles facts:

5+5=10
2+2=4
3+3=6

A double is simply a pair of identical numbers added together. There's a pair of doubles you can <em>subtract </em>1 from to get 6+7, and there's a pair you can <em>add</em> 1 to get the same answer. What are those pairs?

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Suppose the weights of Farmer Carl's potatoes are normally distributed with a mean of 8.0 ounces and a standard deviation of 1.1
svet-max [94.6K]

Answer:

a) 0.9959 = 99.59% probability that the mean weight is less than 9.3 ounces

b) 0.0129 = 1.29% probability that the mean weight is more than 9.0 ounces

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

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.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Mean of 8.0 ounces and a standard deviation of 1.1 ounces.

This means that \mu = 8, \sigma = 1.1

(a) If 5 potatoes are randomly selected, find the probability that the mean weight is less than 9.3 ounces?

n = 5 means that s = \frac{1.1}{\sqrt{5}} = 0.4919

This probability is the pvalue of Z when X = 9.3. So

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{9.3 - 8}{0.4919}

Z = 2.64

Z = 2.64 has a pvalue of 0.9959

0.9959 = 99.59% probability that the mean weight is less than 9.3 ounces

(b) If 6 potatoes are randomly selected, find the probability that the mean weight is more than 9.0 ounces?

n = 6 means that s = \frac{1.1}{\sqrt{6}} = 0.4491

This probability is 1 subtracted by the pvalue of Z when X = 9. So

Z = \frac{X - \mu}{s}

Z = \frac{9 - 8}{0.4491}

Z = 2.23

Z = 2.23 has a pvalue of 0.9871

1 - 0.9871 = 0.0129

0.0129 = 1.29% probability that the mean weight is more than 9.0 ounces

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Answer:

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