Answer:
The p-value is 0.0013. He should reject the null in favor of the alternative.
Step-by-step explanation:
We are given that Members of a soccer team suspect the coin used for the coin toss at the beginning of their games is unfair. They believe it turns up tails less often than it should if it were fair.
The coach of the team decides to flip the coin 100 times and count the number of tails. His trial results in 35 tails.
Let p = <u><em>proportion of occurrence of tail.</em></u>
SO, Null Hypothesis, : p = 0.50 {means that it turns up tails equal to that it should if it were fair}
Alternate Hypothesis, : p < 0.50 {means that it turns up tails less often than it should if it were fair}
The test statistics that would be used here <u>One-sample z-test for proportions;</u>
T.S. = ~ N(0,1)
where, = sample proportion of tails occurrence =
= 0.35
n = sample of trails = 100
So, <u><em>the test statistics</em></u> =
= -3
The value of z test statistics is -3.
Also, P-value of the test statistics is given by;
P-value = P(Z < -3) = 1 - P(Z 3)
= 1 - 0.9987 = <u>0.0013</u>
Since, the P-value of test statistic is less than the level of significance as 0.0013 < 0.01, so we have sufficient evidence to reject our null hypothesis as it will fall in the rejection region due to which <em><u>we reject our null hypothesis</u></em>.
Therefore, we conclude that it turns up tails less often than it should if it were fair.