How Gender Difference Affect College Students

Just need to paraphrase this existing assignment.

2020
Students’ Statistics Anxiety Is Not Strongly Related to Their Gender
Difference.
Quantitative Research Report
Student Details

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Table of Contents
Introduction................................................................................................................................2
Methods......................................................................................................................................3
Participants.............................................................................................................................3
Research Procedure and Ethical Considerations....................................................................4
Measures................................................................................................................................4
Data Analysis.............................................................................................................................5
Box and Whisker Analysis.....................................................................................................5
T-test analysis.........................................................................................................................5
Findings......................................................................................................................................5
Comparative Box and Whisker Plots Analysis Findings:......................................................5
T-test Analysis Findings........................................................................................................7
Conclusions and Implications....................................................................................................7
References..................................................................................................................................9

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Introduction
The researchers, as well as authors, have effectively researched gender difference
among the students in the achievement in a college-level statistics course. Some studies
reflect that anxiety has its influence over different genders and their performance in the
course. The anxiety influences the choice of the students during the course selection, their
performance at exams and also negatively impacts their future career pathways (Rodarte-
Luna & Sherry, 2008). Many researchers have focused on the gender difference as a factor
that influences the performance, but there are certain other factors such as mathematical
knowledge and the student experience that are also required to be considered.
Baloglu (2003) has researched that the anxiety is a controversial point in identifying
the relationship between the statistics and the gender difference, also the research conducted
by him does represent any influence due to the student’s previous mathematical experiences
in the relationship between gender difference and student statistics. Similarly, Rodarte-Luna
and Sherry (2008), found that the student’s statistics anxiety and their learning strategies are
not influenced by the gender difference, however, the gender differences were minimal and
not much supportive. Both articles deny the idea that gender differences have an impact on
the student’s statistics anxiety.
The articles list other factors that are responsible or have more impact on student
statistics anxiety. The factors include procrastination (Rodarte-Luna & Sherry, 2008) and
their previous mathematical experience (Baloglu, 2003). The authors also suggested that
there is a need for further research in this area. Ganley and Vasilyeva effectively focused on
analysing the link between the mathematical anxiety and the student working memory, as a
result, they found that the student's anxiety level is influenced by the working memory as
well as the gender difference and both influences their mathematical performance. The
authors believed that psychologically the female students are more anxious as compared to
the male students, and this anxiety results in the negative impact over the student’s working
memory and results in the poor performance within mathematics (Ganley & Vasilyeva,
2014).
The majority of the research articles that were analysed reflected that the gender
difference contributes towards the student’s statistics anxiety. The data collected also
supports the argument, also comparing the data provides that the male and female difference
is not the only factor contributing towards the anxiety, there are certainly other factors that

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contribute towards producing anxiety among the students. For example, Bandalos et al. (cited
in Rodarte-Luna & Sherry 2008) analysed that when male and female students were focusing
on identifying their success or failure in the statistics, they view their success in different
ways. As a result, it was analysed that the females were more concerned about their
expectation and has set high levels for them, whereas the males were not much concerned and
if they fail, they link them to their abilities in the area of statistics. The result indicates that
there is a need for different learning strategies for both the genders (Rodarte-Luna & Sherry,
2008). However, the available research articles do not provide clarity over which gender
exhibits more superficial learning strategies. Information linking domain-specific learning
strategies to gender in statistics was unable to be found in the research done by the
researchers (Rodarte-Luna & Sherry, 2008).
In this research paper, I will focus upon identifying the student’s past performance in
statistics (using exam results) and will after that analyse the data by taking gender into
consideration as a factor. A survey and an interview will be conducted to analyse the
participants and to explore whether there is any relationship between a student’s gender, level
of anxiety and their performance in statistics. The research will be focused on two major
questions.
1. How does gender difference affect college students’ cognitive ability and learning
strategies?
2. What is their level of stress and anxiety when they attend a statistics class and sit for an
exam?
Methods
Participants
The participants involve a total of 294 students who were enrolled in Advanced
Statistics in Discrete Mathematics courses II at Hope University in South Australia. Among
the participants 27.21% were males and the rest 72.79% were females, also 14% students
were in the first year of their study but somehow managed to enrol themselves into the course
that was offered to the second-year students.

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Research Procedure and Ethical Considerations
The data of the student’s mid-term exam were obtained and recorded for the analysis.
To analyse the anxiety level among the students, a group survey was done and the
information was collected for analysis. Individual interviews were also conducted to obtain
more information about the level of anxiety among the students in relation to the study of the
statistics course.
The research conducted was focused on analysing the psychological status of the
student and his/her performance. The data collected is sensitive and hence confidential. The
survey was conducted anonymously, but still, the data collected in the group survey is also
subject to privacy. The individual interview was effectively conducted in a safe and secure
environment and helped the researchers in gaining more reliable information (Fletcher,
2016), also consent was obtained from the students before the interview and it was made
clear that any uncomfortable situation may lead to immediate pause to interview.
Measures
Exam Scores and the Anxiety Data Scale were used as a measure for this study. The
mean, variance and the P values of the T-test are summarised in Table 1.
Exam Scores: Analysing the exam score helped the researchers in comparing the
achievement of the students in statistics course based on their gender. The test scores for the
genders were analysed and the Five Figure Summaries was used to construct dual Box-and-
Whisker Plot to show any comparative trends, by comparing the median, the upper quartile,
the lower quartile values and the interquartile range. The data display method was also used
to represent the link between student anxiety and gender difference.
Anxiety Scale Data: This data was collected through the student survey; the students were
provided with a scale and were asked to indicate the measure of their anxiety that they
experience during the statistics class. The scale was effectively analysed using the T-test to
show any co-relationship and the null-hypothesis of data.
Variable 1 Variable 2
Mean 1.727891156 45.8537415
Variance 0.198741613
86.7737572
8
Observations 294 294

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Pearson Correlation 0.196668696
Hypothesized Mean
Difference 0
df 293
t Stat
-
81.90168457
P(T<=t) one-tail 2.8676E-204
t Critical one-tail 1.650070786
P(T<=t) two-tail 5.7352E-204
t Critical two-tail 1.968093453
Table 1 T-Test: Paired Two Sample for Means
Data Analysis
Box and Whisker Analysis
Comparative box and whisker plots were used as tools to analyse the data. The data
representation form used by the researchers effectively helps in better understanding the
spread of values for each group. Calculations were performed to identify whether the values
are accurate or not, if not then they can be discounted. The calculation of inter-quartile range
(IQR = Q3 - Q1) helped researchers in better understanding of the distribution of data. The
graph made it easier to compare the groups using the following values: Range = Max – Min,
IQR and Median and two groups could be visually compared (Greenwood, et al., 2012).
T-test analysis
The T-test analysis is used as a tool to identify whether there is a difference between
the means of two groups, which may be related to the certain features that are being
investigated. The researchers focus on assuming that the data is normally distributed during
the test, thus the null hypothesis H0 can be tested. In order to make a judgement, the p value is
calculated and a threshold value α are used (if p ≤ α) to make a judgement as to the null
hypothesis H0, is rejected (Boareto & Caticha, 2014). In this research, the null hypothesis is
“there is no relationship between the gender difference and the statistics anxiety”.
Findings
Comparative Box and Whisker Plots Analysis Findings:
From the raw data, it can be identified that the number of female students taken for
the analysis was higher than compared to the number of male students. It can also be found
that there was more variation in the results of the female group.

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The brown box represents the male group that has a smaller range as compared to the
female group represented as a blue box. There is an outlier in the female group data, the value
16, which can be ignored if it is a transcription error, but if it is a genuine value it must be
considered. The median of the male anxiety scale is also less than that of the female group
which is 42 for male and 47 for female, which indicates that the women’s perception of
anxiety is higher than male.
Figure 1 The comparative box and whisker analysis of data
As stated before, it is required that the outliners are carefully considered while
analysing the data. The data should be checked in order to confirm whether the value 16 is a
result of the error during data filing. If the value is an error, it can be removed and once it is
removed, the next value 23 becomes the data outliner. Again, it is required to be checked to
verify its validity. The researchers should focus on the reasons due to which these values are
lower.
Items Data with outliers Data without the outlier 16 Data without the outlier 16 or 23
Diagrams
Median
(Female) 47 47 47
Median
(Male) 42 42 42
Range of Range = Max – Min Range = Max – Min Range = Max – Min

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Female
Group = 67 – 16 = 51
= 67 – 23 = 44
= 67 – 26 = 41
Range of
Male
Group
Range = Max – Min
= 60 – 20 = 40
Range = Max – Min
= 60 – 20 = 40
Range = Max – Min
= 60 – 20 = 40
IQR
Female
IQR = Q3 – Q1
= 53 – 41 = 12
IQR = Q3 – Q1
= 54 – 42 = 12
IQR = Q3 – Q1
= 54 – 42 = 12
IQR
Male
IQR = Q3 – Q1
= 52 – 37 = 15
IQR = Q3 – Q1
= 52 – 37 = 15
IQR = Q3 – Q1
= 52 – 37 = 15
Table 2 Table shows the box and whisker plots with and without the outliers.
The table indicates that the outliners do not have a significant impact on the measures
of centre. However, when the outliners were removed the range for both the groups were not
affected and remains similar. The median group indicates a greater level of anxiety among
the female groups. The T-test analysis is required to be conducted to explore any influence.
T-test Analysis Findings
The T-test was conducted to identify the relationship between the gender difference
and the statistics anxiety if any. The analysis resulted that [t(293) = -81.90, p ¿ 0.001]. the
results were significant therefore the null hypothesis can be rejected. The use of the T-test
analysis reflected support towards the hypothesis linking the gender difference and statistics
anxiety.
Conclusions and Implications
The research was focused on both methods such as the surveys and the interviews to
identify the link or the relation between the student’s anxiety and gender. The survey also
provided the students with an opportunity to measure their anxiety during the statistics
lectures in their university courses. The interview helped the researchers in identifying other
concerns that were related to having an impact on student anxiety in the subject.
The study resulted in collecting the data and information that reflects the relationship
between gender difference and the student’s anxiety. However, the hypothesis was supported,

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but there may be other factors which can result in causing anxiety among the students and
such factors are required to be taken into consideration. The further research is required to be
focused on identifying and exploring other factors that lead towards causing anxiety among
the students and how effectively students could overcome their anxiety and cam focus upon
improved performance in statistics at the university level.

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References
Baloglu, M., 2003. Individual differences in statistics anxiety among college students.
Personality and individual differences, Volume 34, pp. 855-865.
Boareto, M. & Caticha, N., 2014. T-Test at the Probe Level: An Alternative Method to
Identify Statistically Significant Genes for Microarray Data. Microarrays, 3(4), pp. 340-351.
Fletcher, A., 2016. Assessment As A Student-Driven, Reciprocal Learning Process: A
Recalibrated, Social Cognitive Perspective. [Online]
Available at:
https://www.aare.edu.au/data/2016_Conference/Full_papers/197_Anna_Fletcher.pdf
[Accessed 20 April 2020].
Ganley, C. & Vasilyeva, M., 2014. The Role of Anxiety and Working Memory in Gender
differences in Mathematics. Journal of Educational Psychology, 106(1), pp. 105-120.
Greenwood, D. et al., 2012. Chapter 9 Statistics. In: Essential Mathematics for the Australian
Curriculum Year 10. Melbourne: Cambridge, pp. 558-619.
Rodarte-Luna, B. & Sherry, A., 2008. Sex differences in the relation between statistics
anxiety and cognitive/learning strategies. Contemporary Educational Psychology, Volume
33, pp. 327-344.