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Troyanec [42]
1 year ago
5

Eric is studying people's typing habits. He surveyed 525 people and asked whether they leave one space or two spaces after a per

iod when typing. 440 people responded that they leave one space. Create a 90% confidence interval for the proportion of people who leave one space after a period.
Mathematics
2 answers:
Jobisdone [24]1 year ago
5 0

Answer:  (0.81155,\ 0.86445)

Step-by-step explanation:

The confidence interval for population proportion (p) is given by :_

\hat{p}\pm z^* \sqrt{\dfrac{\hat{p}(1-\hat{p})}{n}}

, where n= sample size

z* = Critical value.

\hat{p} = Sample proportion.

Let p  be the true population proportion of people who leave one space after a period.

As per given , we have

n= 525

\hat{p}=\dfrac{440}{525}=0.838

By z-table , the critical value for 90% confidence interval : z* = 1.645

Now , 90% confidence interval for the proportion of people who leave one space after a period:

0.838\pm (1.645) \sqrt{\dfrac{0.838(1-0.838)}{525}}

0.838\pm (1.645) \sqrt{0.00025858}

0.838\pm (1.645) (0.0160805117)

\approx0.838\pm(0.02645)

=(0.838-0.02645,\ 0.838+0.02645)=(0.81155,\ 0.86445)

Hence, a 90% confidence interval for the proportion of people who leave one space after a period. =(0.81155,\ 0.86445)

hichkok12 [17]1 year ago
3 0

Answer:

The confidence interval is (0.81, 0.87).

Step-by-step explanation:

There's 90% confidence that population proportion is within the interval obtained from the following formula:

\hat{p}\pm z_{\alpha/2}\sqrt{\frac{\hat{p}*(1-\hat{p})}{n}}

Knowing that the sample size, n=525 we obtain the proportion of people from the sample who leave one space after a period as \hat{p}=\frac{440}{525}=0.8381\approx 0.84.

We then look for the critical value:

z_{\alpha/2}=1.645

Now we can replace in the formula to obtain the confidence interval:

0.84\pm 1.645\sqrt{\frac{0.84*(1-0.84)}{525}}= (0.8137; 0.8663)

Therefore we can say that there's 90% probability that the population proportion of people who leave one space after a period lies between the values (0.8137; 0.8663).

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