I just need the final answer (average velocity for entire trip) thanks! :)

Help no links or fake answer or I will report you thanks

likoan [24]

Answer:

Step-by-step explanation:

Given, 

Dimensions of the bed

$= 3in. \: \: by \: \: 2 \frac{2}{3} in. \: \: by \: \: \frac{1}{3} in.$

Therefore, 

Volume of the bed

$= (3 \times 2 \frac{2}{3} \times \frac{1}{3} ) {in}^{3}$

$= (2 \frac{2}{3} \times 1) {in}^{3}$

$= 2 \frac{2}{3} {in}^{3} \: (ans)$

3 0

2 years ago

A pack of 6 batteries of the same type cost £2.79 By calculating the price per battery,

maks197457 [2]

$\large{\rm{\underline{\underline{Answer:}}}}$

Given, 6 batteries for £2.79

(They are of same type, so each of them are of same cost. )

~Simply divide the total price of 6 batteries by 6 to get the price of each battery,

$= \dfrac{£2.79 }{6}$

$= £ \dfrac{279}{100 \times 6}$

$= £ \dfrac{46.5}{100}$

$= £0.465$

Thus, cost of each battery is £ 0.465 (ans)

8 0

2 years ago

A random sample of 9 wheels of cheese yielded the following weights in pounds has a sample mean of 20.90 and a sample variance o

Ronch [10]

Answer:

$2.002 \leq \sigma^2 \leq 11.365$

Step-by-step explanation:

1) Data given and notation

s represent the sample standard deviation

$s^2$ represent the sample variance

n=9 the sample size

Confidence=90% or 0.90

A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population mean or variance lies between an upper and lower interval".

The margin of error is the range of values below and above the sample statistic in a confidence interval.

The Chi Square distribution is the distribution of the sum of squared standard normal deviates .

2) Calculating the confidence interval

The confidence interval for the population variance is given by the following formula:

$\frac{(n-1)s^2}{\chi^2_{\alpha/2}} \leq \sigma \frac{(n-1)s^2}{\chi^2_{1-\alpha/2}}$

On this case we need to find the sample standard deviation with the following formula:

$s=sqrt{\frac{\sum_{i=1}^9 (x_i -\bar x)^2}{n-1}}
The sample variance given was [tex]s^2=3.45$

The next step would be calculate the critical values. First we need to calculate the degrees of freedom given by:

$df=n-1=9-1=8$

Since the Confidence is 0.90 or 90%, the value of $\alpha=0.1$ and $\alpha/2 =0.05$ , and we can use excel, a calculator or a table to find the critical values.