Respuesta :
Answer:
a) [tex]p_v =P(Z>2.05)=1-P(z<2.05)=1-0.980=0.0202[/tex]
b) [tex]p_v =P(Z>-1.84)=1-P(z<-1.84)=1-0.0330=0.967[/tex]
c) [tex]p_v =P(Z>0.4)=1-P(z<0.4)=1-0.655=0.345[/tex]
Step-by-step explanation:
Some previous concepts
The p-value is the probability of obtaining the observed results of a test, assuming that the null hypothesis is correct.
A z-test for one mean "is a hypothesis test that attempts to make a claim about the population mean(μ)".
The null hypothesis attempts "to show that no variation exists between variables or that a single variable is no different than its mean"
The alternative hypothesis "is the hypothesis used in hypothesis testing that is contrary to the null hypothesis"
Hypothesis
Null hypothesis: [tex]\mu=10[/tex]
Alternative hypothesis: [tex]\mu >10[/tex]
If the random variable is distributed like this: [tex]X \sim N(\mu,\sigma)[/tex]
We assume that the variance is known so the correct test to apply here is the z test to compare means, the statistic is given by the following formula:
[tex]z_o=\frac{\bar X -\mu}{\sigma}[/tex]
Since we have the values for the statistic already calculated we can calculate the p value using the following formulas:
Part a
[tex]p_v =P(Z>2.05)=1-P(z<2.05)=1-0.980=0.0202[/tex]
And in order to find the answer using excel we can use the following code:
"=1-NORM.DIST(2.05,0,1,TRUE)"
Part b
[tex]p_v =P(Z>-1.84)=1-P(z<-1.84)=1-0.0330=0.967[/tex]
And in order to find the answer using excel we can use the following code:
"=1-NORM.DIST(-1.84,0,1,TRUE)"
Part c
[tex]p_v =P(Z>0.4)=1-P(z<0.4)=1-0.655=0.345[/tex]
And in order to find the answer using excel we can use the following code:
"=1-NORM.DIST(0.4,0,1,TRUE)"
Conclusions
If we use a reference value for the significance, let's say [tex]\alpha=0.05[/tex]. For part a the [tex]p_v<\alpha[/tex] so then we can reject the null hypothesis at this significance level.
For part b the [tex]p_v>\alpha[/tex] so then we FAIL to reject the null hypothesis at this significance level.
For part c the [tex]p_v>\alpha[/tex] so again we FAIL to reject the null hypothesis at this significance level.