Relationship Between Study Hours And GPA Coursework Example

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Category:
Maths Statistics
Level:
University
Type:
A-Level
Pages:
7
Words:
350

Free Relationship Between Study Hours And GPA Coursework Example

Name Instructor Course Date Math119 What two variables are you comparing? GPA and Study hours Descriptive statistics Categorical v. Categorical: contingency table Categorical v. Quantitative: summary stats on quantitative variable (group by categorical) Quantitative v. Quantitative: correlation coefficient Coefficient -0.2773 No, there is no defined relationship between the GPA and study hours. The negative correlation coefficient indicates these variables are indirectly proportional, signaling the irregular relationship between the variables (Anderson et al. 3). Categorical v. Categorical: split or stacked bar plots Categorical v. Quantitative: boxplots by groups Quantitative v. Quantitative: scatterplot There is no clearly defined relationship between the variables. Data points are scattered all over making it hard to determine there is a relationship between the GPA and study hours. There are no obvious descriptive statistics (Anderson et al. 7). Categorical v. Categorical: Chi-Square Test for Independence (on contingency table) Categorical v. Quantitative: One-way ANOVA Quantitative v. Quantitative: Correlation with hypothesis test AND linear regression If you were comparing two quantitative variables, this is an extra upload space for your results. Everyone else can leave this blank. Hypotheses being tested in the test above. The hypotheses being tested was whether there is a relationship between study hours to the level of GPA that one achieves. The null hypothesis is that there is a relationship between GPA and Study hours. The alternative hypothesis states there is no relationship between GPA and study hours. P-value and Statistical decision The p-value for the hypothesis test was 6.1083 (see the ANOVA table). At 10% significance level, the statistical decision is to reject the null hypothesis. This is because the chi-square test outcome is greater than 10% which is greater than the level of significance. Also, resulting...
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