To display the relationship between two variables, plot the data points with the dependent variable on the y-axis and the independent variable on the x-axis. This is called a two-dimensional graph.
The variable that you want to be able to predict based on another variable is the dependent variable, and the variable that the prediction is based on is the independent variable.
The sample standard deviation expresses the variation within a group of data points. This is relevant when you have multiple data points for the same condition, such as repeated measurements of gas volume at the same temperature. The standard deviation can also be used as an uncertainty range for calculated values.
To quantify the relationship between variables on a two-dimensional graph, use the best-fit function tool in spreadsheet or graphing software to generate the equation that best fits the data. This equation will allow you to calculate dependent values as a function of independent values.
The coefficient of determination (R2) shows the variation between the actual dependent values and the theoretical dependent values that are calculated by plugging the independent values into the best-fit function. The closer the R2 value is to 1, the better the linear function fits the data.
Source: Smaa Koraym at Johns Hopkins University, MD, USA
Here, we show the laboratory preparation for 10 students working individually, with some excess. Please adjust quantities as needed.
1 50-mL beaker |
1 100-mL beaker |
1 250-mL beaker |
1 400-mL beaker |
1 600-mL beaker |
1 500-mL filter flask |
1 Büchner funnel |
1 10-mL graduated cylinder |
1 Watch glass |
1 5-mL volumetric pipette |
1 10-mL volumetric pipette |
1 10-mL capacity pipetter |
1 10-mL volumetric flask |
1 String (18 in) |
1 Silicone vacuum tubing (18 in) |
1 12-in ruler |
1 Rubber adapter |
1 Rubber stopper |
1 Glass stirring rod |
1 Rubber policeman |
1 Disposable pipette |
1 Bottle of deionized water |
1 Lab mat |
1 Box of filter papers (1 filter paper per student) |