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Running head: Conducting and Analyzing Statistical Test 1
Conducting and Analyzing Statistical Tests
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Institutional Affiliation

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Conducting and Analyzing Statistical Test 2
Abstract
Correlation is one of the most important statistical methods used in data analysis. It can
help in the establishment of key relationship between variables. This paper seeks to analyze the
relationship between student anxiety levels before exams and the amount of hours they spent
studying. Analysis majorly involves the Pearson correlation coefficient, however, the paper
comment on suitability of other statistical methods like ANOVA and T-test.

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Running head: Conducting and Analyzing Statistical Test Conducting and Analyzing Statistical Tests Name Institutional Affiliation 1 Conducting and Analyzing Statistical Test Abstract Correlation is one of the most important statistical methods used in data analysis. It can help in the establishment of key relationship between variables. This paper seeks to analyze the relationship between student anxiety levels before exams and the amount of hours they spent studying. Analysis majorly involves the Pearson correlation coefficient, however, the paper comment on suitability of other statistical methods like ANOVA and T-test. 2 Conducting and Analyzing Statistical Test 3 Introduction Correlation analysis, which commonly involves determining the Pearson correlation coefficient “r” in statistics, is important in establishing the nature of relationship, if any, between a pair of statistical variables. Using the correlation coefficient ‘r’, one can establish how strong or weak a relationship is between a pair of variable. The correlation ranges in a scale of -1 to +1; when r leans towards these extremes, then the two variables are very closely related, however, when r equals zero the two variables either have a very weak or no relation at all. When ‘r’ equals +1 the variables are said to be in a perfect positive relationship (the variables are directly proportional). On the contrary, when ‘r’ equals -1 the pair of variables are said to be in a perfect negat ...
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