In this case, the values of one variable do not appear to have any impact on the values of the other variable. No correlation: If the data points on the scatter plot are randomly scattered with no discernible pattern, it indicates no correlation. This means that there is no apparent relationship between the two variables.Ĥ. Equal correlation: If the data points on the scatter plot are distributed in a way that does not show a clear pattern or trend, it suggests an equal correlation or no correlation. In this case, as one variable increases, the other variable tends to decrease.ģ. Negative correlation: If the data points on the scatter plot generally form a pattern that goes from the top-left to the bottom-right, this suggests a negative correlation. This means that as one variable increases, the other variable also tends to increase.Ģ. Positive correlation: If the data points on the scatter plot generally form a pattern that goes from the bottom-left to the top-right, this indicates a positive correlation. It consists of individual data points that are plotted on the graph based on their corresponding values for each variable. In the absence of the actual graph, I can explain how you can make this determination based on the general characteristics of the scatter plot.Ī scatter plot is a graphical representation that displays the relationship between two variables. To determine the type of correlation suggested by a scatter plot, you need to analyze the general pattern or trend of the data points on the graph. This info should help you decide.Ħ.8.8 - Quick Check: Scatter Plots and Regression LinesĦ.8.8- Quick Check: Scatter Plots and Regression Lines No correlation means the dots are scattered al over the place. Negative correlation goes from upper left to lower right. Positive correlation goes from lower left to upper right. 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.10 answers For Lesson 8: Scatter Plots and Regression Lines: 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 2013įertility Rate (number of children per mother)
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