Samples and Hypothesis Testing and Variance

Samples and Hypothesis Testing and VarianceANOVA is the analysis of variance, it involves the
Part Onetesting of joint hypothesis, and the ANOVA table
Perform hypothesis testing on one variable's data.for a multiple regression model is demonstrated in
(Choose either the intrinsic or extrinsic column.)the table below
Perform a t-test by formulating a null and anSource of variation
alternative statement, choosing an acceptableSum of squires
significance value, selecting the test statistic andDegrees of freedom
determining its value from the sample data,Mean sum of squares
comparing the observed value to the critical valueDue to regression
obtained and determining whether to reject or fail(ESS)
to reject the null hypothesis.B1∑y1x1 +B2 ∑y1x2
We test the hypothesis that the mean value of2
the intrinsic satisfaction is greater than one,(B1∑y1x1 +B2 ∑y1x2)/ 2
The null hypothesis             Ho: U = 0Due to Residue
The alternative hypothesis   Ha: U ≠ 0(RSS)
We will test the test statistics at 95% level∑e2n-3
So we find the value of T at 5%, which will be a∑e2/ n-3
two tail test, however we will choose a sampleTotal variation
from our population which will contain 20(TSS)
observations.∑ y12n-1
The T critical from the table is 2.08596∑ y12/ n-1
T calculated isAccording to a the academic journal by Munerver
Z = X/Standard deviationOlcum named job satisfaction, job satisfaction is
Z = 3.565/ 0.888094important in an organisation, this study involved
Z calculated = 4.014216132 academic participants, according to this study
From the above calculations the T calculated >there was a high correlation between job
T critical, therefore we reject the null hypothesissatisfaction and commitment and occupation.
that the mean is equal to zero.The T test for various measures and the
T test and Z testANOVA was undertaken to test for any
The Z test is used to get the area under themeaningful differences between job satisfaction
normal distribution, the value of the area underand commitment and how this relates to age,
the normal distribution is equal to one, andgender, marital status experience and job title.
therefore the value obtained from the Z table canAccording to the test on gender and marital
also obtain the probability of an outcome. The Zstatus it was found out that there was no
test is mostly used to test single means and thedifference in job satisfaction according to gender
difference between two means.and marital status, however the study showed
The T test is used to construct a confidencethat there was a significant difference in job
interval given the degrees of freedom and thesatisfaction in reference to age, the study
significant level of test example 95% 99% orshowed that academics aged 41 and above had
98%, the value is also used to test the statisticalhigher job commitments and satisfaction than the
significance of a parameter once you estimateacademics aged between 20 and 30, further
the regression, the T test is undertaken tothere was also a significant difference in job
determine the statistical significance throughsatisfaction in reference to experience and job
hypothesis testing of the autonomous value andtitle, whereby people with experience have higher
the slope or slopes of the regression line.job satisfaction than the inexperienced.
Part TwoReferences
Using the Business Source Premier Database andData base
or the API Inform Global database in the LibraryData base
provide research on Job Satisfaction and write upMunevver Olcum Cetin (2006) the Relationship
a short 1 page report on the topic. The articlebetween Job Satisfaction, Occupational and
you choose should include the terms JobOrganizational Commitment of Academics,
Satisfaction AND ANOVA, or Job SatisfactionMarmara University, Istanbul
AND One-Way ANOVA. Cite all sources used.Bluman A. G.
Job satisfaction and ANOVA