Homework3
Chapter21
Question7
H_{1}:μ> μ_{0}ORH_{1}:μ< μ_{0}
H_{1}:μ≠200
S= 30
N= 64
X= 218
T=H_{1}0
Standarderror of H1
T= 640 ≠ 200
0.05
T= 64/0.05
T= 1280
Question11
H_{1}:μ≠200
S= 30
N= 9
X= 218
T=9 – 0≠ 200
0.05
9/0.05
T=180
Comparisonof the results
Thedata in question 10 gives null hypothesis because the test resultshave deviated to 1280, which is far away from the approximated figureof 200. On the other hand, the test in given by the data in question11 approximates the hypothesis figure at 180. The 180 figure isclose to the initially approximated figure of 200. This implies thatquestion ten generates a null hypothesis while the data in question11 generated an alternative hypothesis (Evans et al. 36).
Question17
H_{0}= 15 %
H_{1}=20 %
N= 1200
Thedecision rule is set at 1% significance level
CriticalZ value 2.57 is used for hypothesis test
Z=√ pq/n
Z= √ {(0.02 x 0.02) ÷1200} = 0.0115
Z= (0.2 – 0.15) ÷ (0.0115) = 4.3478
The4.3478 Z value is greater the 2.57 critical value. Therefore, this isan alternative hypothesis because it is supported by the informationprovided.
Question7, Ch. 22
7.How independent t tests differ from:
A.
a)Ttests are only applicable in cases when an individual has only acouple of groups to compare, but ANOVA groups are designed forcomparing several groups following the tactics applied in ttests(Evans et al. 20).
b)Ttest data sample should be normally distributed , and thepopulation should have equal variance. On the other hand, the anovatests samples are selected randomly and independtly (Evanset al. 21).
B.
Thettests are used in comparison of two independent data groups whilethe paired ttest is used for comparing paired data. In many cases,paired data is used for tracking the process in which change occursin a variable. For example, size of a metal bar before heating andafter heating (Evans et al. 25).
C.
Thettests are used in comparison of two independent data groups whilethe paired ttest while the X^{2}tests are intended for determining the probability of observeddistribution coming to chance or turning out positively as projected(Evans et al. 11).
D.the Ztest difference from ttest

Ztest statistical hypothesis test follows normal distribution ttests often observes student’s Tdistribution

Ttests are best suited for handling small data (n<30) while Ztests are best suited for handling slightly bigger information (n>30).

Ttests have higher adaptability than Ztests since the latter often require meeting specific conditions in order to become dependable. Moreover, Ztests often come with numerous processes that can meet the desired outcome

When the standard deviation has been determined, Ztests are often more preferred than ttests
Question11
H_{1}:μ≠200
S= 30
N= 9
X= 218
T=9 – 0≠ 200
0.05
9/0.05
T=180
Comparisonof the results
Thedata in question 10 gives null hypothesis because the test resultshave deviated to 1280, which is far away from the approximated figureof 200. On the other hand, the test in given by the data in question11 approximates the hypothesis figure at 180. The 180 figure isclose to the initially approximated figure of 200. This implies thatquestion ten generates a null hypothesis while the data in question11 generated an alternative hypothesis (Evans et al. 36).
17)Queation 11, Ch. 22
1.Parameter of interest: "n" = 1,200 2. Nullhypothesis Ho: μ = 0.05 3. Alternative hypothesis H_{1}:μ ≠ 0.2 significant level = 0.05
Delta= 0.2 – 0.05 = 0. 15
Z=(0.2 0.05)/ (0.2/√1200)
Z= 0.15/ (02/34.64101615137755)
Z=0.15÷ 0.00575026918963
Z= 26.0857353
Workscited
Evans,Merran, Nicholas A. J. Hastings, and J B. Peacock. StatisticalDistributions.New York, NY [u.a.: Wiley, 2000. Print.