Remember a correlation does not imply causation. There are many other factors that could influence both, such as medical care and education. The fertility rate does not necessarily cause the life expectancy to change. Caution: just because there is a correlation between higher fertility rate and lower life expectancy, do not assume that having fewer children will mean that a person lives longer. It appears that there is a trend that the higher the fertility rate, the lower the life expectancy. 2) If the value of y decreases with the value of x, then we can say that the variables have a negative correlation. This correlation would probably be considered moderate negative correlation. 1) If the value of y increases with the value of x, then we can say that the variables have a positive correlation. It looks a little stronger than the previous scatter plot and the trend looks more obvious. Graph 2.5.4: Scatter Plot of Life Expectancy versus Fertility Rate for All Countries in 2013Īgain, there is a downward trend. Let’s see what the scatter plot looks like with data from all countries in 2013 ("World health rankings," 2013). The trend is not strong which could be due to not having enough data or this could represent the actual relationship between these two variables. What this says is that as fertility rate increases, life expectancy decreases. Graph 2.5.3: Scatter Plot of Life Expectancy versus Fertility Rateįrom the graph, you can see that there is somewhat of a downward trend, but it is not prominent. Note: Always start the vertical axis at zero to avoid exaggeration of the data. The vertical axis needs to encompass the numbers 70.8 to 81.9, so have it range from zero to 90, and have tick marks every 10 units. The horizontal axis needs to encompass 1.1 to 3.4, so have it range from zero to four, with tick marks every one unit. Examine the overall pattern and the dispersion of data points. Plot the variables on a graph, with one variable on the x-axis and the other on the y-axis. In this case, it seems to make more sense to predict what the life expectancy is doing based on fertility rate, so choose life expectancy to be the dependent variable and fertility rate to be the independent variable. Scatter Plots: Complement the analysis with scatter plots to visualize the relationships between variables. Sometimes it is obvious which variable is which, and in some case it does not seem to be obvious. To make the scatter plot, you have to decide which variable is the independent variable and which one is the dependent variable. Though there are a few outliers (cities along the northwest coast of the US that have temperate winters, such as Portland, OR) there is a strong, linear trend. For example, the scatterplot of latitude and January temperatures had negative direction, as the greater the latitude, the colder the temperature. \): Life Expectancy and Fertility Rate in 2013 Countryįertility Rate (number of children per mother) Scatter plots are described as linear or nonlinear.
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