Ho: p = 0.4
Ha: p < 0.4
p value = ~10%
The amount of men the companies has as excutives could be explained enitrly by random sampling variation. In ohter words, there is a 10% chance that if the hypothesis of 0.4 is true, than this outcome has a ikelyhood ok 10%, which is too high to reject the null.
Random: We must assume that the sample was slected randomly 10%: 122 is less thn 10% of population of flyers
h0: p=0.9
ha: p<0.9
p value = 0.02
The companies claim is probably wrong. Assuming the companies claim is correct, there is only a 2% chance that these results would happen. Therefore, it’s more probable that the hypothesis is wrong and that passangers actually get their bads reutrned at a lower rate.
H0: p=0.136
p>0.136
random: assume that these 220 peopl working on the filmw ere representative of the population in nevada 10%: 220 people is less than 10%
Model: N(0.136, sqrt(0.136*0.863/220)
p value = 0
We can conclude that this variation is increably unlikely, assuming the normal rate of death due to cancer for the group. The radtiona most likely caused parts of the cancer.
h0: p=0.6
ha: p>0.6
random: teacher says students are representative 10%: her class is less than 10% of all students who take APs
N(0.6, sqrt(0.6*0.4/54))
p value = 0.23
There is not comelling evidence to reject our null that there is a 0.6 chance that her students will get a 3 or higher. There is a 23% chance that her students scores wer ecuased by random variation, which is too high to reject the null hypothesis.