Quantitative Analysis (Research Paper Sample)

Quantitative Analysis
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Introduction
This is a research project on the effects of anxiety and performance factors among sports people. It is a quantitative research, which classifies people into three different groups depending on their levels of anxiety such as low, medium and high. The values of the anxiety levels are transformed from qualitative to quantitative measures by assigning numerical values (Gubrium and Holstein 2000, p73). The research involves conducting two statistical analyses with the data provided in order to answer the study questions. The statistical tests and the findings from the analyses will indicate whether the relationship exist between individuals’ anxiety levels and their abilities to perform. The hypothesis on which the study is based is that anxious people do not have the potentials to demonstrate high quality service delivery (Denzin & Lincoln 2011, p61). In this regard, the tests are interested in the performance of people with varying ranges of anxiety in the eyes of observers (audience).
Research Question
This research has two fundamental study problems as the guiding principles. The first question is on whether the subjects of varying levels of anxiety can perform equally or not, before the any given audience. This will necessitate the test of linear correlation as a statistical analysis of the relationship between the anxiety levels and the individual performances. The second fundamental study problem is on whether or not there is a connection between the natural levels of anxiety and the psychological as well as the mechanical (physical) factors observed in the individual performances. With this question, it will be vital to test and analyze the linearity of the correlation between the anxiety scores and the mean club head velocity.
Methodology
This is a quantitative research since it purely uses quantitative data for the sake of analysis. All qualitative data variables have been used in quantitative form. A good example is the grouping of the anxiety levels and the corresponding anxiety scores for each level. Of course, the study questions require a qualitative argument establishing the relationship between two distinct variables in the same data set. However, the argument requires an informed ground based on the behavior of the quantitative data during the analysis. The methods of data analysis are informative, descriptive and cognitive in the sense that it informs the audience about the details of the group of workers, describes them about anxiety levels and scores and finally refers to the visible attributes of the anxiety groups to provide the arguments. It combines different data analysis options for a holistic description in order to use one analysis to verify the results of the other tests and analysis.
Analysis
As mentioned earlier, this research will conduct two fundamental quantitative analyses to be able to answer the study questions (Creswell 2008, p54). The analysis of the data takes place in SPSS version 16, as the statistical software of choice. There will be two stages of statistical analysis as follows:
Linear Correlation Analysis
ANOVA (Analysis of Variance)
Linear Correlation Analysis
Linear correlation analysis runs in two stages. The first stage is a test of correlation between the level of anxiety and the Heat Rate. This answers the first study question. The second stage of linear correlation analysis is tested between the anxiety levels and the Mean Club Head Velocity. The results are shown in the Appendix Page.
ANOVA
The second analysis in this research is the One Way analysis of variance (ANOVA) for all variables that have been tested in the previous analysis. The ANOVA shows the variance between the anxiety group and all the three other variables anxiety score, heat rate, new error from target and the mean club head velocity.
The outputs are as shown in the Appendix section.
Discussion
From the correlation analysis, the coefficient of relationship between the Anxiety group and heat rate is 0.53. This shows an existence of a positive relationship, but of a low magnitude (Holstein and Gubrium 2012, p49). On the other hand, the correlation coefficient between the Heat rate and anxiety group is 0.79. This is a positive influence of a higher magnitude. The second correlation coefficient analysis measures the relationship between heat rate and the anxiety score, 0.045 while anxiety score to heat rate has a coefficient of 0.089, whose impact is greater than in the previous test. The analysis of variance between the variables reflect a scenario in which the research finds the difference between the means of anxiety score and all the other three variables. The result is:
Anxiety score against Heat rate = 0.219
Anxiety score against Mean club head velocity = 0.589
Anxiety score against New Error from target = 0.079
Evaluation
The analyses were successful and relevant in the study of the relationship bet...