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Xelga [282]
3 years ago
10

The mean income per person in the United States is $50,000, and the distribution of incomes follows a normal distribution. A ran

dom sample of 10 residents of Wilmington, Delaware, had a mean of $60,000 with a standard deviation of $10,000. At the 0.05 level of significance, is that enough evidence to conclude that residents of Wilmington, Delaware, have more income than the national average?
a. State the null hypothesis and the alternate hypothesis.b. State the decision rule for 0.05 significance level.Reject H0 if t > ____c. Compute the value of the test statistic.d. Is there enough evidence to substantiate that residents of Wilmington, Delaware, have more income than the national average at the 0.05 significance level?
Mathematics
1 answer:
gulaghasi [49]3 years ago
5 0

Answer:

We conclude that the residents of Wilmington, Delaware, have more income than the national average.

Step-by-step explanation:

We are given the following in the question:  

Population mean, μ =  $50,000

Sample mean, \bar{x} = $60,000

Sample size, n = 10

Alpha, α = 0.05

Sample standard deviation, s = $10,000

a) First, we design the null and the alternate hypothesis

H_{0}: \mu = 50000\text{ dollars}\\H_A: \mu > 50000\text{ dollars}

We use one-tailed(right) t test to perform this hypothesis.

c) Formula:

t_{stat} = \displaystyle\frac{\bar{x} - \mu}{\frac{s}{\sqrt{n}} }

Putting all the values, we have

t_{stat} = \displaystyle\frac{60000 - 50000}{\frac{10000}{\sqrt{10}} } = 3.162

Now, t_{critical} \text{ at 0.05 level of significance, 9 degree of freedom } = 1.833

b) Rejection Rule:

If the calculated t-statistic is greater than the the critical value, we rect the null hypothesis.

Since,                  

t_{stat} > t_{critical}

We fail to accept the null hypothesis and reject it.We accept the alternate hypothesis.

d) There is enough evidence to conclude that the residents of Wilmington, Delaware, have more income than the national average.

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The 95% confidence interval for the difference would be given by (-1.776;0.376)

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Step-by-step explanation:

Previous concepts

A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".

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Let put some notation  

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x: 6.4 2.6 7.7 10.5 11.7 5.8 4.3 2.8

y: 6.7 2.4 7.4 8.1 8.6 6.4 3.9 2.7

The differences defined as d_i = y_i -x_i and we got:

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\bar d=\frac{\sum_{i=1}^n d_i}{n}

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\bar d=-0.7 represent the sample mean for the difference

\mu_d population mean (variable of interest)

s_d=1.32 represent the sample standard deviation

n=8 represent the sample size  

Confidence interval

The confidence interval for the mean is given by the following formula:

\bar d \pm t_{\alpha/2} *\frac{s_d}{\sqrt{n}}  (1)

In order to calculate the critical value t we need to find first the degrees of freedom, given by:

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Since the Confidence is 0.95 or 95%, the value of alpha=0.05 and \alpha/2 =0.025, and we can use excel, a calculator or a table to find the critical value. The excel command would be: "=-T.INV(0.025,8)".And we see that t_(\alpha/2)=2.306

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