This is a powerpoint presentation that discusses how lower GDP in parts of the world and in specific countries seems to be indicators of general poverty, shortness of life expectancy of male and female adults, and higher incidencies of infanct mortality. Many in the world may not be aware of the situation and there seems to be a lack of awareness of the personal tragedies that these regions face.
The purpose of this research is to use descriptive data to measure the relationships, by country and region, of how lower GDP contributes to lower life expectancy rates among adults and higher rates of infant mortality.
In the powerpoint, There are graphs that showcases the dependent variable and the independent variable. There are also regression analysis information that follows each graph.
My question is on each graph, what is the strength of the relationship between the two variables? Is it positive or negative relationship. Is there a reason to believe that the variables are related?
On the regression analysis sections that follows each graph, does the data suggest that there is a negative or positive correlation between the variables?
The information in this powerpoint is listed as Graph A-GDP per capita and region of the world and the regression analysis A1 and down to Graph G and Regression Analysis G1
Correlation measures the strength of the relationship between two variables. It is represented by the letter r.
If there is a strong correlation between two variables, r will be close to -1 or 1, and the graph of the data will look roughly like a line. If there is not a correlation between the variables, r will be close to 0, and the graph of the data will look more like a cloud of ...