Answer:
a) 
b) 
c) 
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: 
Alternative hypothesis: 
If the random variable is distributed like this: 
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:

Since we have the values for the statistic already calculated we can calculate the p value using the following formulas:
Part a

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

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

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
. For part a the
so then we can reject the null hypothesis at this significance level.
For part b the
so then we FAIL to reject the null hypothesis at this significance level.
For part c the
so again we FAIL to reject the null hypothesis at this significance level.