To understand the concept of independent and dependent variables, one should understand the meaning of variables. Variables are defined as the properties or kinds of characteristics of certain events or objects.
Independent variables are variables that are manipulated or are changed by researchers and whose effects are measured and compared. The other name for independent variables is Predictor[s]. The independent variables are called as such because independent variables predict or forecast the values of the dependent variable in the model.
The groups are along the horizontal axis, while the dependent variable, learning outcomes, is on the vertical. From the graph, method 4 has the best results. A one-way ANOVA will tell you whether these results are statistically significant. Learn more about interpreting boxplots.
Now, imagine that you are studying people’s height and weight. Specifically, do height increases cause weight to increase? Consequently, height is the independent variable on the horizontal axis, and weight is the dependent variable on the vertical axis. You can use a scatterplot to display this type of data.
It appears that as height increases, weight tends to increase. Regression analysis will tell you if these results are statistically significant. Learn more about interpreting scatterplots.