Statistical Tests for Different Research Problems - Desklib

21.4
F-test
The problem in this case is to determine the difference between the results of the previous
research design and the current study through determining whether the variances of the research
from the 2 researches are statistically different. As such, an F-test is used which examines the
difference in variances. In examining the difference in variance, the following formulae is used:
Fcritical ¿ Variance 1
Variance 2
To address the reaserch problem the following hypothesis can be formulated:
Ho: There is a difference in variances
Ha: There is no difference in variances.
Where the researcher should reject the null hypothesis if the tabular F-statistic is less than the
computed. If the null is rejected, then there are differences in the results of the two researches.
21.7
F-test
The data for this scenario is quantitative i.e. age. As such, to examine whether there is a
difference in the month of birth for creative artists an F-test for difference for comparison of
variances is adopted. Hence the hypothesis to be formulated is:
Ho: There is a difference in variances
Ha: There is no difference in variances.
The F-statistic is then given by:

Fcritical ¿ Variance 1
Variance 2
Where the researcher should reject the null hypothesis if the tabular F-statistic is less than the
computed, otherwise do not reject.
21.8
Chi-Square
To test for a relationship between sexual codes of primitive tribes and their behavior towards
neighboring tribes involves the use of qualitative data which is categorical in nature given the
basis of the sexual codes as described in the research problem. As such, a Chi-square test is used
to examine the relationship at a given level of significance i.e. 0.05, 0.01 etcetera.
Where, Or,c is the observed frequency count at level r of sexual codes and level c behavior
towards their neighboring tribes, while Er,c is the expected frequency count at level r of sexual
codes and level c is behavior towards their neighboring tribes.
You reject the null hypothesis if the computed Chi-square is greater than the tabular Chi-Square.
21.12
ANOVA (F-test and Chi-Square test)
The difference between the effects of treatment and control on different factors is measured
through use of ANOVA which uses both the chi-square to test for independence and F-test to test
the difference of variances i.e. is there a dependence among the test variables and are the results
statistically different for each variable. To investigate whether there is a relationship between the
research variables i.e. operating room and survival of amputees, an independence test is

conducted to determine whether the two variables are related hence a chi-square test is adopted.
The data for this study is qualitative.
21.13
This problem involves a repeated measure experiment which is aimed determine the difference
between the activity of other rats given the presence of urine chemicals in male rats. As such, in
order to examine the difference between activities of control and treatment groups, an F-test is
used which will enable determination of whether activities of rats given the presence of urine and
during absence of urine are statistically different. To conduct the analysis of the experiment, after
collecting data, the researcher computes the variances of the two groups and conducts an F-test
to obtain an F-statistic using the variance from group 1 and that of group 2 using the formula:
F-tests use qualitative data as in this case.
21.14
Chi-square
To investigate the effectiveness of relaxation training on the subsequent performance of college
students in public speaking. The researcher uses a control group which in this case are the
randomly assigned students while the treatment group are those subjected to relaxation training.
As such, the data is discrete categorical and the researcher will conduct a Chi-square test to
evaluate the treatment effect. The null hypothesis assumes that there is no difference on the