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3 years ago

I JUST NEED #13 please and thnx

Mathematics

1 answer:

emmainna [20.7K]3 years ago

3 0

$\bf \cfrac{18}{32}\implies \cfrac{2\cdot 3\cdot 3}{2\cdot 2\cdot 2\cdot 2\cdot 2}\implies \cfrac{3\cdot 3}{2\cdot 2\cdot 2\cdot 2}\implies \boxed{\cfrac{9}{16}}\qquad \checkmark \\\\[-0.35em] ~\dotfill\\\\ \cfrac{27}{48}\implies \cfrac{3\cdot 3\cdot 3}{2\cdot 2\cdot 2\cdot 2\cdot 3}\implies \cfrac{3\cdot 3}{2\cdot 2\cdot 2\cdot 2}\implies \boxed{\cfrac{9}{16}}\qquad \checkmark$

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Answer:

a) $29.4-1.96\frac{7}{\sqrt{10}}=25.06$

$29.4+1.96\frac{7}{\sqrt{10}}=33.74$

So on this case the 95% confidence interval would be given by (25.06;33.74)

b) $z=\frac{29,4-25}{\frac{7}{\sqrt{10}}}=1.988$

$p_v =P(z>1.988)=0.0234$

If we compare the p value and the significance level given $\alpha=Step-by-step explanation:Previous conceptsA confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval". 
The margin of error is the range of values below and above the sample statistic in a confidence interval. 
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean". 
Part a
Data given: 30 30 42 35 22 33 31 29 19 23
We can calculate the sample mean with the following formula:[tex] \bar X = \frac{\sum_{i=1}^n X_i}{n}= 29.4$ the sample mean

$\mu$ population mean (variable of interest)

$\sigma=7$ represent the population standard deviation

n=10 represent the sample size

95% confidence interval

The confidence interval for the mean is given by the following formula:

$\bar X \pm z_{\alpha/2}\frac{\sigma}{\sqrt{n}}$ (1)

Since the Confidence is 0.95 or 95%, the value of $\alpha=0.05$ and $\alpha/2 =0.025$ , and we can use excel, a calculator or a table to find the critical value. The excel command would be: "=-NORM.INV(0.025,0,1)".And we see that $z_{\alpha/2}=1.96$

Now we have everything in order to replace into formula (1):

$29.4-1.96\frac{7}{\sqrt{10}}=25.06$

$29.4+1.96\frac{7}{\sqrt{10}}=33.74$

So on this case the 95% confidence interval would be given by (25.06;33.74)

Part b

What are H0 and Ha for this study?

Null hypothesis: $\mu \leq 25$

Alternative hypothesis : $\mu>25$

Compute the test statistic

The statistic for this case is given by:

$z=\frac{\bar X-\mu_o}{\frac{\sigma}{\sqrt{n}}}$ (1)

z-test: "Is used to compare group means. Is one of the most common tests and is used to determine if the mean is (higher, less or not equal) to an specified value".

We can replace in formula (1) the info given like this:

$z=\frac{29,4-25}{\frac{7}{\sqrt{10}}}=1.988$

Give the appropriate conclusion for the test

Since is a one side right tailed test the p value would be:

$p_v =P(z>1.988)=0.0234$

Conclusion

If we compare the p value and the significance level given $\alpha=0.05$ we see that $p_v$ so we can conclude that we have enough evidence to reject the null hypothesis.

8 0

3 years ago

A manufacturer uses production method to produce steel rods. A random sample of 17 steel rods resulted in lengths with a standar

Arisa [49]

Answer:

$\chi^2 =\frac{17-1}{12.15} 22.09 =15.87$

Traditional method

We can find a critical value in the chi square distribution with df =16 who accumulates $\alpha/2 =0.05$ of the area on each tail and we got:

$\chi^2_{crit}= 7.962$

$\chi^2_{crit}=26.296$

Since the calculated value is between the two critical values we don't have enough evidence to conclude that the true deviation is NOT significantly different from 3.5 cm

Confidence level method

We can find the p value like this

$p_v =2*P(\chi^2 >15.87)=0.92$

Since the p value is higher then the significance level we have enough evidence to FAIL to reject the null hypothesis and we can conclude that the true deviation is NOT significantly different from 3.5 cm

Step-by-step explanation:

Data provided

$n=17$ represent the sample selected

$\alpha=0.1$ represent the significance

$s^2 =4.7^2 =22.09$ represent the sample variance

$\sigma^2_0 =3.5^2 =12.15$ represent the value to check

Null and alternative hypothesis

We want to verify if the new production method has lengths with a standard deviation different from 3.5 cm, so the system of hypothesis would be:

Null Hypothesis: $\sigma^2 = 12.15$

Alternative hypothesis: $\sigma^2 \neq 12.15$

The statistic for this case is given by:

$\chi^2 =\frac{n-1}{\sigma^2_0} s^2$

The degrees of freedom are:

$df =n-1= 17-1=16$

$\chi^2 =\frac{17-1}{12.15} 22.09 =15.87$

Traditional method

We can find a critical value in the chi square distribution with df =16 who accumulates $\alpha/2 =0.05$ of the area on each tail and we got:

$\chi^2_{crit}= 7.962$

$\chi^2_{crit}=26.296$

Since the calculated value is between the two critical values we don't have enough evidence to conclude that the true deviation is significantly different from 3.5 cm

Confidence level method

We can find the p value like this

$p_v =2*P(\chi^2 >15.87)=0.92$

Since the p value is higher then the significance level we have enough evidence to FAIL to reject the null hypothesis and we can conclude that the true deviation is significantly different from 3.5 cm

7 0

3 years ago