A school administrator claims that less than 50% of the students of the school are dissatisfied
by the community cafeteria service. Test this claim by using sample data obtained from a survey of
500 students of the school where 54% indicated their dissatisfaction of the community cafeteria
service. Use 𝐠= 0.05.
1) Complete the table.
n X p₀ z p-value
a) 120 21 5%
b) 138 32 7%
c) 200 45 10%
d) 392 102 18%
e) 612 236 20%
f) 100 40 8%
g) 248 51 10%
h) 312 100 12%
When the sample size is large the sample proportion is normally distributed.
With "n=500," the Central Limit Theorem applies.
The following null and alternative hypotheses for the population proportion needs to be tested:
"H_0:p\\ge0.50"
"H_a:p<0.50"
This corresponds to a left-tailed test, for which a z-test for one population proportion will be used.
Evidence:
Based on the information provided, the significance level is "\\alpha = 0.05\n\n," and the critical value for a left-tailed test is "z_c = -1.6449."
The rejection region for this left-tailed test is "R = \\{z: z < -1.6449\\}."
The z-statistic is computed as follows:
Since it is observed that "z =3.5777 \\ge-1.6449= z_c," it is then concluded that the null hypothesis is rejected.
Using the P-value approach:
The p-value is "p=P(Z<3.5777)= 0.999827," and since "p=0.999827>0.05=\\alpha," it is concluded that the null hypothesis is not rejected.
Therefore, there is not enough evidence to claim that the population proportion "p" is less than 0.50, at the "\\alpha = 0.05" significance level.
"\\def\\arraystretch{1.5}\n \\begin{array}{c:c:c:c:c}\n n & X & p_0 & z & p-value \\\\ \\hline\n 120 & 21 & 0.05 & 6.2828 & 0 \\\\\n \\hdashline\n 138 & 32 & 0.07 & 7.4534 & 0\\\\\n \\hdashline\n 200 & 45 & 0.10 & 5.8926 & 0\\\\\n \\hdashline\n 392 & 102 & 0.18 & 4.1333 &0.000036 \\\\\n \\hdashline\n 612 & 236 & 0.20 & 11.4800 & 0\\\\\n \\hdashline\n 100 & 40 & 0.08 & 11.7954& 0\\\\\n \\hdashline\n 248 & 51 & 0.10 & 5.5457&0 \\\\\n \\hdashline\n 312 & 100 & 0.12 &10.8990 &0 \\\\\n\n\\end{array}"
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