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3 years ago

What is the Kinetic energy of a 2000 kg bus that is moving at 30m/s? Explain please

Mathematics

1 answer:

agasfer [191]3 years ago

4 0

There's a formula for that.

KE = (1/2)mv²

... = (1/2)(2000 kg)(30 m/s)²

... = 900,000 kg·m²/s²

... = 900,000 J

_____

It is helpful to know the relationship between kilograms, meters, seconds, and Newtons or Joules.

1 J = 1 kg·m²/s²

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The town of Hayward (CA) has about 50,000 registered voters. A political research firm takes a simple random sample of 500 of th

timama [110]

Answer: (0.076, 0.140)

Step-by-step explanation:

Confidence interval for population proportion (p) is given by :-

$\hat{p}\pm z_{\alpha/2}\sqrt{\dfrac{\hat{p}(1-\hat{p})}{n}}$

, where $\hat{p}$ = sample proportion.

n= sample size.

$\alpha$ = significance level .

$z_{\alpha/2}$ = critical z-value (Two tailed)

As per given , we have

sample size : n= 500

The number of Independents.: x= 54

Sample proportion of Independents $\hat{p}=\dfrac{x}{n}=\dfrac{54}{500}=0.108$

Significance level 98% confidence level : $\alpha=1-0.98=0.02$

By using z-table , Critical value : $z_{\alpha/2}=z_{0.01}=2.33$

The 98% confidence interval for the true percentage of Independents among Haywards 50,000 registered voters will be :-

$0.108\pm (2.33)\sqrt{\dfrac{0.108(1-0.108)}{500}}\\\\=0.108\pm2.33\times0.013880634\\\\=0.108\pm0.03234187722\\\\\approx0.108\pm0.032=(0.108-0.032,\ 0.108+0.032)=(0.076,\ 0.140)$

Hence, the 98% confidence interval for the true percentage of Independents among Haywards 50,000 registered voters.= (0.076, 0.140)

8 0

3 years ago

A swimming pool is drained at the end of each summer. Fifteen gallons of water are removed per minute. How much does the amount

BartSMP [9]

Multiplying -15 by 60 yields -900, so the amount of water in the pool changes by -900 gallons in one hour.

7 0

3 years ago

Graph the function f(x) = -42-4+ 5 on the axes below. You must plot the

valentina_108 [34]

Answer:

- attached graph

- Horizontal Asymptote: y = 5

- twon whole number points are (4,4) and (5,1)

Step-by-step explanation:

- Exponential functions have a horizontal asymptote. The equation of the horizontal asymptote

y = -4^(x-4) + 5

= -4^(4-4) + 5

= -4^(0) + 5

= -1 + 5

= 4

y = -4^(x-4) + 5

= -4^(5-4) + 5

= -4^(1) + 5

= -4 + 5

= 1

7 0

2 years ago

The sum of 8 times a number and 5 is equal to 3

saw5 [17]

8x+5=3
8x=3-5
8x=-2
X=-1/4

5 0

3 years ago

Read 2 more answers

Andrew plans to retire in 32 years. He plans to invest part of his retirement funds in stocks, so he seeks out information on pa

Debora [2.8K]

Answer:

a) 0.0885 = 8.85% probability that the mean annual return on common stocks over the next 40 years will exceed 13%.

b) 0.4129 = 41.29% probability that the mean return will be less than 8%

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 z-score 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 p-value, 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 8.7% and standard deviation 20.2%.

This means that $\mu = 8.7, \sigma = 20.2$

40 years:

This means that $n = 40, s = \frac{20.2}{\sqrt{40}}$

(a) What is the probability (assuming that the past pattern of variation continues) that the mean annual return on common stocks over the next 40 years will exceed 13%?

This is 1 subtracted by the pvalue of Z when X = 13. So

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

By the Central Limit Theorem

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