Given that the mean hospital stay is \mu= 7.1 days and to test that in 2002 whether the stay will be less due to the initiative aimed at reducing the healthcare costs a sample of n = 40 patients is selected which results in sample mean stay of "\\bar{X}= 6.85" days sand the sample standard deviation is s = 7.01 days.
Thus based on the claim the hypotheses are:
"H_0: \\mu = 7.1 \\\\\n\nH_1 : \\mu < 7.1"
Based on the hypothesis it will be a left tailed test.
Since the sample size is greater than 30 and the population standard deviation is unknown hence t-distribution is applicable for hypothesis testing. So, a degree of freedom is used which is calculated as df = n-1= 40-1 =39.
Test statistic:
"t= \\frac{\\bar{X}- \\mu}{s \/ \\sqrt{n}} \\\\\n\nt = \\frac{6.85 -7.1}{7.01 \/ \\sqrt{n}} = -0.226"
Rejection region:
Reject the H if P-value is less than 0.05.
P-value:
The P-value is computed using the excel formula for t-distribution which is =T.DIST(-0.226, 39, TRUE), thus the P-value is computed as 0.4114.
Conclusion: Since the P-value is greater than 0.05 hence we fail to reject the null hypothesis and conclude that there is insufficient evidence to support the claim that the mean days has decreased.
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