Graphical Descriptive Statistics

Graphical Descriptive Statistics

Name

Institution

Graphical Descriptive Statistics

Some of the two articles that have used descriptive statistics in reaching a conclusion are from Riccardo et al., (2011) and Engebretsen et al., (2008). The publication by Riccardo et al., (2011) was an infant mortality survey, which revealed that high quality perinatal and maternal services should be improved in Palestine. Similarly Engebretsen et al., (2008) examined child morbidity and mortality in sub-Saharan Africa, which revealed that poor household wealth, gender, family size, and age were associated with growth among Ugandan infants. This paper analyzes how the aforementioned publication used descriptive statistics to communicate their ideas.

        To begin with, Riccardo et al., (2011) used bar charts, a pie chart, and line graphs to communicate his ideas. For the pie chart, the independent variable was the causes of infant deaths among Palestine refugees (ordinal type of measurement) while the independent variable was the frequency of occurrence (scale type of measurement). For the line graph, the independent variable was years (nominal type of measurement) while the dependent variable was the infant mortality rate (scale type of measurement). For the bar graphs, scale types of measurement acted as the dependent variables while nominal type of measurement acted as the independent variables.

        The main graph used by Engebretsen et al., (2008) was a box plot. This owes to the reality that the box plot was meant to identify any outliers of the data used. Descriptive statistics such as the mean and variance were also used in analyzing the data. For instance, the variance was used to check the deviation of the observed variables from the mean. Ultimately, the mean was also used to compare the anthropometric indices according to sex.

References

Engebresten, S, M, I., Tylleskar, T., Wamani, H., Karamagi, C., Tumwine, K. J. (2008).