How can scatterplots be used to identify relationships between variables?

1 What is a correlation?

A correlation is a measure of how closely two variables are related to each other. It indicates the direction and strength of the relationship, but not the cause and effect. A correlation can be positive, negative, or zero. A positive correlation means that as one variable increases, the other variable also increases. A negative correlation means that as one variable increases, the other variable decreases. A zero correlation means that there is no relationship between the two variables.

2 How to create a scatterplot?

To create a scatterplot, you need two variables that are measured on a continuous scale, such as height, weight, temperature, or time. You can use Excel, Google Sheets, R, Python, or online calculators to plot the data on a coordinate plane. The steps for creating a scatterplot involve choosing one variable as the independent variable (x-axis) and the other as the dependent variable (y-axis), labeling the axes with the names and units of the variables, plotting the data points by using the values of the variables as coordinates, and adding a title and legend if necessary.

3 How to interpret a scatterplot?

To interpret a scatterplot, you need to look at the shape, direction, and spread of the data points. The shape tells you if the relationship is linear or nonlinear. A linear relationship means that the data points form a straight line or a close approximation. A nonlinear relationship means that the data points form a curve or a more complex pattern. The direction tells you if the correlation is positive or negative. A positive correlation means that the data points slope upward from left to right. A negative correlation means that the data points slope downward from left to right. The spread tells you how strong or weak the correlation is. A strong correlation means that the data points are clustered tightly around the line or curve. A weak correlation means that the data points are scattered widely around the line or curve.

4 How to measure the correlation?

To measure the correlation, you need to calculate a numerical value that summarizes the degree of the relationship. The most common measure is the Pearson correlation coefficient, denoted by r. It ranges from -1 to 1, where -1 indicates a perfect negative correlation, 1 indicates a perfect positive correlation, and 0 indicates no correlation. You can use formulas, software, or online calculators to find r. However, you should also consider the context and the quality of the data before drawing conclusions from r.

5 How to use scatterplots for critical thinking?

Scatterplots can help you develop your critical thinking skills by allowing you to explore data, test hypotheses, and identify patterns or trends. You can use them to compare different variables and see how they are related, as well as to spot outliers or anomalies that deviate from the general pattern. Additionally, scatterplots can be used to assess the validity and reliability of the data and the sources, evaluate the assumptions and limitations of the analysis and methods, and generate questions and hypotheses for further investigation or research.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?