On the other hand, a Scatter Plot Chart uses dots to display associations and correlations present in your raw data. You can use the chart to extract trend and patterns insights into raw data. Graph-A is a Line Chart while Graph-B is a Scatter Plot.Ī Line Chart is a visualization design that displays information as data points connected by straight line segments. Let’s visualize the tabular data below using a Scatter Plot Visualization. Is there a correlation between the age and height of the genders understudy? Gender The Scatter Plot Chart is ideal, especially if your goal is to uncover hidden associations between key variables. The chart uses dots to reveal the correlation between the variables under study. Scatter Plot Definition & Scatter Plot ExampleĪ Scatter Plot (also called x-y Graph) is a visualization design best suited to displaying relationships between key data points. If multiple lines are used, they may be used for comparison purpose as well. When there are smaller changes, this chart is best to use rather than any other charts. This chart is best suited to track short and long term changes. Some continuous data will change over time the weight of a child in its first year or the temperature in a room throughout the day, a person’s age after certain years. Line chart is not for every data but if you have continuous data that you would like to represent through a chart then a line chart is a good option.Ĭontinuous data is data that can take any value. Remember a correlation does not imply causation.So when should you select a Line Graph as your premier visualization in your data stories? When to Choose Line Graphs? 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. This correlation would probably be considered moderate negative 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. 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. 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. \): Life Expectancy and Fertility Rate in 2013 Countryįertility Rate (number of children per mother)
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