Respuesta :
Answer:
Case n =5
[tex]z=\frac{4.8-5}{\frac{0.5}{\sqrt{5}}}=-0.894[/tex] Â
Case n =15
[tex]z=\frac{4.8-5}{\frac{0.5}{\sqrt{15}}}=-1.549[/tex] Â
Case n = 40
[tex]z=\frac{4.8-5}{\frac{0.5}{\sqrt{40}}}=-2.530[/tex] Â
P value
Case n =5
[tex]p_v =P(z<-0.894)=0.186[/tex] Â
Case n =15
[tex]p_v =P(z<-1.549)=0.0606[/tex] Â
Case n =40
[tex]p_v =P(z<-2.530)=0.0057[/tex] Â
Step-by-step explanation:
Data given and notation Â
[tex]\bar X=4.8[/tex] represent the sample mean
[tex]\sigma=0.5[/tex] represent the population standard deviation
[tex]n[/tex] sample size Â
[tex]\mu_o =5[/tex] represent the value that we want to test Â
[tex]\alpha[/tex] represent the significance level for the hypothesis test. Â
z would represent the statistic (variable of interest) Â
[tex]p_v[/tex] represent the p value for the test (variable of interest) Â
State the null and alternative hypotheses. Â
We need to conduct a hypothesis in order to check if the mean is lower than 5, the system of hypothesis would be: Â
Null hypothesis:[tex]\mu \geq 5[/tex] Â
Alternative hypothesis:[tex]\mu < 5[/tex] Â
Since we know the population deviation, is better apply a z test to compare the actual mean to the reference value, and the statistic is given by: Â
[tex]z=\frac{\bar X-\mu_o}{\frac{\sigma}{\sqrt{n}}}[/tex] (1) Â
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". Â
Calculate the statistic Â
We can replace in formula (1) the info given like this: Â
Case n =5
[tex]z=\frac{4.8-5}{\frac{0.5}{\sqrt{5}}}=-0.894[/tex] Â
Case n =15
[tex]z=\frac{4.8-5}{\frac{0.5}{\sqrt{15}}}=-1.549[/tex] Â
Case n = 40
[tex]z=\frac{4.8-5}{\frac{0.5}{\sqrt{40}}}=-2.530[/tex] Â
P-value Â
Since is a left tailed test the p value would be: Â
Case n =5
[tex]p_v =P(z<-0.894)=0.186[/tex] Â
Case n =15
[tex]p_v =P(z<-1.549)=0.0606[/tex] Â
Case n =40
[tex]p_v =P(z<-2.530)=0.0057[/tex] Â
Using the z-distribution, it is found that:
For n = 5, the p-value is of 0.1867.
For n = 15, the p-value is of 0.0606.
For n = 40, the p-value is of 0.0057.
At the null hypothesis, it is tested if the pH is of 5, that is:
[tex]H_0: \mu = 5[/tex]
At the alternative hypothesis, it is tested if the pH is of less than 5, that is:
[tex]H_1: \mu < 5[/tex]
We have the standard deviation for the population, thus, the z-distribution is used. The test statistic is given by:
[tex]z = \frac{\overline{x} - \mu}{\frac{\sigma}{\sqrt{n}}}[/tex]
The parameters are:
- [tex]\overline{x}[/tex] is the sample mean.
- [tex]\mu[/tex] is the value tested at the null hypothesis.
- [tex]\sigma[/tex] is the standard deviation of the sample.
- n is the sample size.
For this problem, the values of the parameters are: [tex]\overline{x} = 4.8, \mu = 5, \sigma = 0.5[/tex]
For a sample of 5, we have that [tex]n = 5[/tex], and hence:
[tex]z = \frac{\overline{x} - \mu}{\frac{\sigma}{\sqrt{n}}}[/tex]
[tex]z = \frac{4.8 - 5}{\frac{0.5}{\sqrt{5}}}[/tex]
[tex]z = -0.89[/tex]
The p-value is the probability of finding a sample mean pH below 4.8, which is the p-value of z = -0.89.
Looking at the z-table, z = -0.89 has a p-value of 0.1867, hence, the p-value of the test is of 0.1867.
For a sample of 15, we have that [tex]n = 15[/tex], and hence:
[tex]z = \frac{\overline{x} - \mu}{\frac{\sigma}{\sqrt{n}}}[/tex]
[tex]z = \frac{4.8 - 5}{\frac{0.5}{\sqrt{15}}}[/tex]
[tex]z = -1.55[/tex]
[tex]z = -1.55[/tex] has a p-value of 0.0606, hence, this is the p-value of the test.
For a sample of 40, we have that [tex]n = 40[/tex], and hence:
[tex]z = \frac{\overline{x} - \mu}{\frac{\sigma}{\sqrt{n}}}[/tex]
[tex]z = \frac{4.8 - 5}{\frac{0.5}{\sqrt{40}}}[/tex]
[tex]z = -2.53[/tex]
[tex]z = -2.53[/tex] has a p-value of 0.0057, hence, this is the p-value of the test.
A similar problem is given at https://brainly.com/question/24146681