Week 8

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Walden University *

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6701

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Sociology

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May 13, 2024

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docx

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Quantitative Research and Analysis Louise Johnson Dr. Stephen Connor Rice
The assignment of this week is testing the correlation and bivariate between two variables selected from Afrobarometer dataset. The relationship is significant to research. Association is one of the most widely used tools in statistics (Magnusson, n.d.) The Pearson correlation test, a bivariate test, looks at the correlation of two variables. Using the Afrobarometer dataset, we can look at the relationship between age and live poverty index. The research question for these two variables is: is there a correlation between the age and the live poverty index. My research question is to check whether there is a significant relation between the age and the lived index poverty. Hypothesis H0: ρ = 0 (“relation between age and lived Poverty Index does not exist”) H1: ρ ≠ 0 (“relation between age and lived Index do exist”) The Correlational research design is appropriate for this study since the researcher does not attempt to manipulate the variables and only measure them and look for relations between the dependent and independent variables (Frankfort-Nachmias and Leon-Guerrero, 2018). In my research the dependent variable is Lived Poverty Index and estimated on ratio scale of estimation while the independent variable is age and estimated on ratio scale of estimation Below is the output of Pearson correlation coefficients among the ages and lived poverty index. Where r=0.044 and p-value < 0.05, therefore I conclude that correlation coefficient value is significant. From the value of r = 0.044, we can clearly say that there is a weak correlation between age and Lived Poverty Index. The mean rise in the number of age has no impact on Lived poverty index. Additionally, we can say that the principle caused of poverty isn't aged instead creates by changing patterns in a nation's economy, high illiteracy level, rate of divorce, which is high, having, country overpopulated, diseases such as AIDS and malaria, (Lusted, Marcia Amidon (2010) and problem in environment inadequate rainfall. (Harrison, Paul, 1993)
Extreme weather such as drought, flooding, and rain are some of the most causes of poverty by the weather. The linear regression analysis output as obtained from SPSS is given below.
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