Working with Inferential Statistics

Running head: WORKING WITH INFERENTIAL STATISTICS 1
Working with Inferential Statistics
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WORKING WITH INFERENTIAL STATISTICS 2
Working with Inferential Statistics
Independent Sample t-Test
To determine if children with exposure to movies produced before 1980 triggered more
injuries compared to those with exposure after 1980, a one-sample t-test is conducted. One-
sample t-test aims to establish if the two samples originate from a given mean. Before
conducting the test, several assumptions are made. First, the data distribution between the two
groups are independent (Trafimow & MacDonald, 2017). Second, the dependent variable used in
the analysis needs to be normally distributed. Also, there should be outliers observed in the data
points. Based on these assumptions, the t-test results are summarized in the tables below.
Table 1.
Independent Samples Test
Levene's Test
for Equality
of Variances t-test for Equality of Means
F Sig. t df
Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95%
Confidence
Interval of the
Difference
Lower Upper
Injuries Equal variances
assumed
9.439 .003 3.100 72 .003 1.379 .445 .492 2.265
Equal variances
not assumed
3.914 71.100 .000 1.379 .352 .676 2.081
The p-value of the test is 0.003, which is below the significance level of 0.05. Therefore,
the assumption of equal variances not assumed holds. From the sig. (2-tailed) results, the means
of the two populations are not equal. The majority of the injuries involve children exposed to
movies before 1980.

WORKING WITH INFERENTIAL STATISTICS 3
Which Group Caused More Injuries
One-way ANOVA is used to determine if a significant difference exists in the means of
each group (Ali & Bhaskar, 2016). The main assumption used in performing the ANOVA test is
that the groups display homogeneity in their variances (Mertler & Reinhart, 2016). The null
hypothesis for the one-way ANOVA test is that all the groups have equal means. The results for
the test are displayed in the table below.
Table 2.
ANOVA Results
Sum of
Squares df Mean Square F Sig.
Between Groups 105.461 35 3.013 .761 .791
Within Groups 150.390 38 3.958
Total 255.851 73
From the ANOVA test results above, the p-value is 0.791 which is above the significance
level of 0.05. The null hypothesis is hence withheld that the groups have equal means. Therefore,
the children exposed to movies in 1937 – 1960, 1961 – 1989, and 1990 – 1999; caused
approximately the same number of injuries.
The statistical analysis test applied in this paper is essential in my prospectus. Inferential
statistics involve the use of data analysis techniques to deduce the underlying properties and
probability distribution of a given population (Crowder, 2017). This involves performing
hypothesis tests and deriving estimates of the characteristics of the sample pollution examined.
Thus, the inferential statistics knowledge acquired in this paper would be applied in my