"a)i) p\\prime=\\frac{290}{500}=0.58\\text{ is a point estimate of population proportion}\\\\\nii)p\\prime n=(0.58)500>5, (1-p\\prime)n=(0.42)500>5"
So the binomial distribution can be estimated by the normal
distribution.
"\\alpha=0.05\\\\\n(p\\prime-z_{\\alpha\/2}\\sqrt{\\frac{p\\prime (1-p\\prime)}{n}},p\\prime+z_{\\alpha\/2}\\sqrt{\\frac{p\\prime (1-p\\prime)}{n}})\\\\\nz_{0.025}=1.96\\\\\n(0.58-1.96\\sqrt{\\frac{(0.58)(0.42)}{500}},0.58+1.96\\sqrt{\\frac{(0.58)(0.42)}{500}})\\\\\n(0.537;0.623)\\text{ is the confidence interval}.\\\\\nb)i) H_0:p=0.6, H_1:p<0.6\\text{ (left-sided)}\\\\\nii) z_{stat}=\\frac{p\\prime-p}{\\sqrt{\\frac{p(1-p)}{n}}}=\\frac{0.58-0.6}{\\sqrt{\\frac{(0.6)(0.4)}{n}}}=-0.913\\\\\niii) z_{cr}=1.64\\\\\n(-\\infty,-1.64)\\text{ is the critical region}\\\\\niv) z_{stat}>-z_{cr}. \\text{ So we accept } H_0: p=0.6."
"v)"There is no evidence that the population proportion of successes is less than 0.6.
c) The conclusion of part (b) does not follow from (a) because we have one-tailed hypothesis test ("\\alpha=0.05") and "95"% confidence interval.
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