What is nominal level of measurement

If we compare the p value and the significance level given $\alpha=0.05$ we see that $p_v>\alpha$ so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, so we can conclude that the population mean is NOT significant different from 410 at 5% of significance.

b) $p_v =2*P(z$

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, so we can conclude that the population mean is significant different from 410 at 5% of significance.

c) The expplanation why we have different outcomes is because for part a we use a higher standard error compared to part b. So we have enough evidence on part b to reject the null hypothesis that we no have significant difference from 410.

Step-by-step explanation:

1) Part a

Previous concepts and data given

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".

$\bar X=386$ represent the sample mean

$\sigma=60$ represent the population standard deviation

n=9 represent the sample selected

$\alpha=0.05$ significance level

State the null and alternative hypotheses.

We need to conduct a hypothesis in order to check if we have significant difference on the mean, the system of hypothesis would be:

Null hypothesis: $\mu = 410$

Alternative hypothesis: $\mu \neq 410$

If we analyze the size for the sample is < 30 but we know the population deviation so is better apply a z test to compare the actual mean to the reference value, and the statistic 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".

Calculate the statistic

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

$z=\frac{386-410}{\frac{60}{\sqrt{9}}}=-1.2$

P-value

Since is a two side test the p value would be:

$p_v =2*P(z$

Conclusion

If we compare the p value and the significance level given $\alpha=0.05$ we see that $p_v>\alpha$ so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, so we can conclude that the population mean is NOT significant different from 410 at 5% of significance.

2) Part b

State the null and alternative hypotheses.

The system of hypothesis not changes:

Null hypothesis: $\mu = 410$

Alternative hypothesis: $\mu \neq 410$

Same statistic:

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

Calculate the statistic

But now the population deviation changes $\sigma=30$ . We can replace in formula (1) the info given like this:

$z=\frac{386-410}{\frac{30}{\sqrt{9}}}=-2.4$

P-value

Since is a two side test the p value would be:

$p_v =2*P(z$

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, so we can conclude that the population mean is significant different from 410 at 5% of significance.

7 0

4 years ago

Bamboo shoots grow at a constant rate of 129 cm per day . If a shoot of bamboo is 6.5 meters long in monday morning .whAt is the

Mrrafil [7]

You would first convert meters to centimeters which would equal 650cm. so then you take 129 and multiply it by 4 because that is how many days it will be growing. you take the product of 129 and 4 (which is 516) and add it to the 650 that you started with on monday morning. your answer will be

1,166cm or 11.66 meters

3 0

3 years ago