8.        Random sampling from two normal populations produced the following results:
x1 = 412Â Â Â Â Â Â Â s1 = 128Â Â Â Â Â Â n1 = 150
x2 = 405Â Â Â Â Â s2 = 54Â Â Â Â Â Â Â n2 = 150
(a.) Can we infer at the 5% significant level that m1
is greater than m2 ?
(b.) Repeat part (a) decreasing the standard deviations to: s1 = 31 and s2 = 16
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9.            In random samples of 25 from eah of two normal populations we found the following statistics:
x1 = 524Â Â Â Â Â Â s1 = 129
x2 = 469Â Â Â Â Â s2 = 141
(a.) Estimate the difference between the two population means with 95% confidence (b.) Repeat part (a) increasing the standard deviations
to: s1 = 255 and s2 = 260
8 (a) Null hypothesis: "m{\\scriptscriptstyle 1}\u2264m{\\scriptscriptstyle 2}"
Alternative hypothesis: "m{\\scriptscriptstyle 1}>m{\\scriptscriptstyle 2}"
Since both sample sizes are greater than 30, we can use Z-score
According to the form of the null hypoyhesis, we should use right-tailed test
"P(Z>Z{\\scriptscriptstyle cr})=0.05\\implies Z{\\scriptscriptstyle cr}=1.645"
The test value is:
"Z{\\scriptscriptstyle test}={\\frac {(x{\\scriptscriptstyle 1}-x{\\scriptscriptstyle 2})} {\\sqrt{({\\frac {s^2{\\scriptscriptstyle 1}} {n{\\scriptscriptstyle 1}}} + {\\frac {s^2{\\scriptscriptstyle 2}} {n{\\scriptscriptstyle 2}})}}}}={\\frac {412-405} {\\sqrt{{\\frac {128^2} {150}}+{\\frac {54^2} {150}}}}}={\\frac 7 {11.3}}=0.62"
There is not enoughg evidencve to reject null hypothesis on th 0.05 significance level, so m1
is not greater than m2
(b) Now s1 = 31 and s2 = 16, which means our test statistic would be
"Z{\\scriptscriptstyle test}={\\frac {(x{\\scriptscriptstyle 1}-x{\\scriptscriptstyle 2})} {\\sqrt{({\\frac {s^2{\\scriptscriptstyle 1}} {n{\\scriptscriptstyle 1}}} + {\\frac {s^2{\\scriptscriptstyle 2}} {n{\\scriptscriptstyle 2}})}}}}={\\frac {412-405} {\\sqrt{{\\frac {31^2} {150}}+{\\frac {16^2} {150}}}}}={\\frac 7 {2.85}}=2.456"
There is enoughg evidencve to reject null hypothesis on th 0.05 significance level, so m1
is greater than m2
9 (a) The difference between two sample means with 95% confidence is
"a \\in (""(x{\\scriptscriptstyle 1} - x{\\scriptscriptstyle 2})-Cr{\\scriptscriptstyle 0.95}*{\\sqrt{({\\frac {s^2{\\scriptscriptstyle 1}} {n{\\scriptscriptstyle 1}}} + {\\frac {s^2{\\scriptscriptstyle 2}} {n{\\scriptscriptstyle 2}})}}};(x{\\scriptscriptstyle 1} - x{\\scriptscriptstyle 2})+Cr{\\scriptscriptstyle 0.95}*{\\sqrt{({\\frac {s^2{\\scriptscriptstyle 1}} {n{\\scriptscriptstyle 1}}} + {\\frac {s^2{\\scriptscriptstyle 2}} {n{\\scriptscriptstyle 2}})}}})"
Since we have small sample sizes, then it is appropriate to use t-statistic(two-tailed) with n - 1 degrees of freedom
"P(T(24)>Cr{\\scriptscriptstyle 0.95})=0.025\\implies Cr = 2.063"
"(x{\\scriptscriptstyle 1} - x{\\scriptscriptstyle 2})*Cr{\\scriptscriptstyle 0.95}*{\\sqrt{({\\frac {s^2{\\scriptscriptstyle 1}} {n{\\scriptscriptstyle 1}}} + {\\frac {s^2{\\scriptscriptstyle 2}} {n{\\scriptscriptstyle 2}})}}})=(55-2.063*38.2;55+2.063*38.2)=(-23.8;133.8)"
(-23.8;133.8) is the 95% confidence interval
(b) for s1 = 255 and s2 = 260 we have
"(x{\\scriptscriptstyle 1} - x{\\scriptscriptstyle 2})*Cr{\\scriptscriptstyle 0.95}*{\\sqrt{({\\frac {s^2{\\scriptscriptstyle 1}} {n{\\scriptscriptstyle 1}}} + {\\frac {s^2{\\scriptscriptstyle 2}} {n{\\scriptscriptstyle 2}})}}})=(55-2.063*72.84;55+2.063*72.84)=(-95.27;205.29)"
(-95.27;205.29) is tha 95% confidence interval
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