Answer:
The probability that the person is between 65 and 69 inches is 0.5403
Step-by-step explanation:
Mean height =
Standard deviation =
We are supposed to find What is the probability that the person is between 65 and 69 inches i.e.P(65<x<69)
At x = 65
Z=-0.4
Refer the z table for p value
P(x<65)=0.3446
At x = 69
Z=1.2
P(x<69)=0.8849
So,P(65<x<69)=P(x<69)-P(x<65)=0.8849-0.3446=0.5403
Hence the probability that the person is between 65 and 69 inches is 0.5403
Answer:
We conclude that this is an unusually high number of faulty modems.
Step-by-step explanation:
We are given that while conducting a test of modems being manufactured, it is found that 10 modems were faulty out of a random sample of 367 modems.
The probability of obtaining this many bad modems (or more), under the assumptions of typical manufacturing flaws would be 0.013.
Let p = <em><u>population proportion</u></em>.
So, Null Hypothesis, : p = 0.013 {means that this is an unusually 0.013 proportion of faulty modems}
Alternate Hypothesis, : p > 0.013 {means that this is an unusually high number of faulty modems}
The test statistics that would be used here <u>One-sample z-test</u> for proportions;
T.S. = ~ N(0,1)
where, = sample proportion faulty modems=
= 0.027
n = sample of modems = 367
So, <u><em>the test statistics</em></u> =
= 2.367
The value of z-test statistics is 2.367.
Since, we are not given with the level of significance so we assume it to be 5%. <u>Now at 5% level of significance, the z table gives a critical value of 1.645 for the right-tailed test.</u>
Since our test statistics is more than the critical value of z as 2.367 > 1.645, so we have sufficient evidence to reject our null hypothesis as it will fall in the rejection region due to which <u><em>we reject our null hypothesis</em></u>.
Therefore, we conclude that this is an unusually high number of faulty modems.
Answer:
a. We get 56 heads out of 100 tosses.
We will use one sample proportion test
x = 56
n = 100
Formula of test statistic =
=
=
refer the z table for p value
p value = 0.8849
a. We get 560 heads out of 1000 tosses.
We will use one sample proportion test
x = 560
n = 1000
Formula of test statistic =
=
=
refer the z table for p value
p value = .000148
p value of part B is less than Part A because part B have 10 times the number the tosses.