Given that many more people are working from home, an independent research
agency, reSEARCH, is investigating how that affects the number of hours worked each
day. Another factor of interest is whether or not each participant has children since
their presence in a home could also affect the amount of time spent working.
reSEARCH conducted a two-factor, independent-measures study investigating the
average number of hours worked each week based on work location (from home or at
work) and the presence of children in the home (children or no children). The results
are summarized in the table below.
Using a significance level of
a=0.05, conduct a two-factor ANOVA F test by filling in
the missing information below and answering all of the questions. Express any
numerical answers rounded to two decimal places. Be sure to use unrounded values
within all calculations (even those that have already been expressed as a rounded
number).
Main Effect A: Work Location
Hypotheses:
H_(0):\mu _(A_(F\Pi ))=\mu _(A_(AW))
H_(1):\mu _(A_(III ))!=\mu _(A_(AII ))
Test Statistic:
◻
Critical Value:
F_(crit _(()()A))=
Decision:
O reject the null hypothesis
fail to reject the null hypothesis
Main Effect B: Children in the Home
Hypotheses:
H_(0):\mu _(B_(1))=\mu _(B_(C))=\mu _(B_(N))
H_(1):\mu _(B_(1))=\mu _(B_(C))!=\mu _(B_(NC))
Test Statistic:
F_(stat_(\Delta ,))=
Critical Value
F_(crit _(()()D))=
Decision:
O reject the null hypothesis
fail to reject the null hypothesis
Interaction
Hypotheses:
H_(0) : there is no interaction between work location and presence of children
H_(1) : there is interaction between work location and presence of children
Test Statistic
F_(stat_(A\times A))=
Critical Value
Decision:
O reject the null hypothesis
fail to reject the null hypothesis
Overall Conclusion
What can you conclude based on the above results?
