Business Research Module

Business Research Module
BUSINESS RESEARCH MODULE

Business Research Module
Question one
The diagram represents the process or stages of a statistical study. The first step involves
identification of the population from which to collect our data. Population refers to the total
count of objects or people that will be considered viable for our study.
The next step involves drawing a random sample from the population to be used for calculating
the parameters that are of interest. A sample refers to a smaller group of objects or people,
representing the large group, that will be admitted into the study.
The third stage of the process involves calculation of the statistic of interest basing on the data
that was collected from the population sample. Descriptive statistics, for example, mean, median
or proportions could be calculated at this stage.
The fourth and final stage involves interpretation and reporting the findings from the study. The
statistics calculated based on the sample responses could also be calculated by collecting data
from the whole population.
Question two
The table presents results of independent t test results for the variable RER. The independent-
samples t-test (or independent t-test, for short) compares the means between two independent
groups on the same continuous, dependent variable. The test to be performed is whether the
means are different or not. The null hypothesis for the independent t-test is that the population
means from the two independent groups are not different:
H0: u1 = u2
In most cases, it is being looked at to see if it can be shown that the null hypothesis is rejected
and the alternative hypothesis accepted, which is that the population means are not equal:
HA: u1 ≠ u2

Business Research Module
The Levene’s test for equality of variances presents a p-value greater than 0.05 implying that we
fail to reject the null hypothesis of equal variances. We therefore conclude that the variables
RER from the two groups under investigation are homoscedastic, that is they have equal
variances.
The independent t-test for equality of means has p-values greater than 0.05 when equal and
unequal variances are assumed. P-values greater than 0.05 imply that we fail to reject the
hypotheses of equal means when equal and unequal variances are assumed. We thereby conclude
that there is no difference in the means of the RER variable from the two population groups.
Question three
The table presents results of one-way ANOVA analysis. The one-way analysis of variance
(ANOVA) is used to determine whether there are any statistically significant differences between
the means of two or more independent (unrelated) groups. The null hypothesis for ANOVA is
that the mean (average value of the dependent variable) is the same for all groups. The
alternative or research hypothesis is that the mean is not the same for all groups.
The significant (p-value) is interpreted in order to either reject or fail to reject the null
hypothesis.
It can be seen that the significance (p-value) equals 0.022 which is less than 0.05, and therefore
at the 5% we reject the null hypothesis of no difference in the mean of the variable enjoyable in
the two groups. We therefore conclude that there is statistical difference in the enjoyable mean
for the two groups.