Introduction

The purpose of today's assignment is to practice using Google sheets to make a graph. It is often helpful to present experimental data in a visual way, and creating a graphical representation with x/y data is a common and useful approach. While creating a graph, there are several steps and points to keep in mind to make sure that your graph represents your data accurately.

1. Identify your independent variable and your dependent variable. The independent variable is what you, as the scientist, can control. It is usually the first dimension that you measure. The dependent variable represents the response-- it is what you want to know and usually represents the second dimension that you measure.
2. In your spreadsheet, always set up your data columns so that your independent variable is on the left and the dependent variable is on the right.
3. Label your columns with the dimensions and units.
4. Adjust the number of zeroes in each column to reflect the precision of your measurement; that is, the data in your spreadsheet should have the correct number of significant figures.

Setting up the spreadsheet carefully is the first step to making sure that your graph turns out well. When you make the graph, the following elements are essential.

1. Your axes must be labeled with the dimension and the unit. This is slightly easier if you have labeled the data columns.
2. Your axis values should represent the precision of the measurement. Again, this is easier if you have already adjusted the number of zeroes in the spreadsheet.
3. All of your data points must be visible. You may find that you need to adjust the minimum or maximum axis values.
4. For linear data (virtually all of the data you encounter in general chemistry labs will be linear), add a linear trendline. The trendline will generate a best-fit linear equation that approximates your data values. Display the equation and R² value on the chart. The R² value is a measure of how closely your actual data matches the line. In general, the R² value should be between 0.9 and 1.0. If your value is less than 0.9, it indicates that your data is "noisy" or perhaps you were measuring a non-linear phenomenon. If your R² value is exactly 1.0, this can also be a red flag for real-world data. Real data is never perfect.
5. Delete the title. It is unnecessary.

Name:
	Volume of liquid (mL)	Mass of liquid (g)
	1.03	13.54
	2.10	27.34
	3.06	41.00
	3.99	54.12
	5.02	67.57