Statistical Analysis
The best statistical test for the data given is the t-test because it is the best method for analyzing and comparing two variables whose means and standard deviation are given. It is also relevant in this case because it is accurate and easier to compute (Ott & Longnecker, 2010).
Null hypothesis
There is no correlation between the understanding of Christian doctrine and the amount of church attendance
Alternative hypothesis
There is a strong correlation between the understanding of Christian doctrine and the amount of church attendance.
Given that there are two variables in the data, the degrees of freedom would be n-1,
=2-1=1
The variables therefore have 1 degree of freedom, with 1% (0.01) level of significance (Ott & Longnecker, 2010).
T-test= [x̂1-x̂2]/√ {s1/n1+s2/n2}
=[55.2000-37.8000]/√{34.49895/10 + 4.26354/10}
=[17.4]/{3.449895+.426354}
=17.4/3.876249
=3.71
There is a positive correlation between the two variables.
The p-value is less than 0.01 (0.000) and since this value is below the conventionally accepted level of significance of 0.01 (1%), that is p<0.05, we reject the null hypothesis (Nelson, 2013). This implies that there is no statistically significant difference between understanding of Christian doctrine and the amount of church attendance (Khan, 2013).
P= P (T≥t; Ho) =P (T≥3.71; Ho) ≈P (Z≥3.71) <0.05, where Z stands for a standard normally distributed variable
The p-value is given as 0.000 and therefore, the difference between the means is not statistically significant and different form zero at the 1% significance level (Currell, 2015).
References
Currell, Graham. (2015). Scientific Data Analysis. Oxford Univ Pr.
Khan, R. M. (2013). Problem solving and data analysis using Minitab: A clear and easy guide to six sigma methodology.
Nelson, S. L. (2013). Excel 2007 data analysis for dummies. Hoboken, N.J: John Wiley & Sons.
Ott, L., & Longnecker, M. (2010). An introduction to statistical methods and data analysis. Belmont, CA: Brooks/Cole Cengage Learning.