SelfGuide

InLab: the lab experiment

1. Setting up the lab:

Before you start the lab, review the objectives and procedures you will follow. Take notes as you set up your experiment and calibrate instruments to help you document your experimental protocol so that you may use it later when writing the Methods section of your lab report.

On a sheet of paper or in your lab manual or in a formal lab notebook, list the lab materials you'll be using and describe the set-up for this experiment. Take notes about potential sources of uncertainty so that you may refer to them when you are writing the Discussion section of your lab report. You may want to or may be required to draw and label the instrument(s) you'll be using.

(See below for definitions of underlined words.)

(Refer to the web version of this document for example lab notebook pages.)

Lab notebook:

Keeping accurate lab notebooks is very important for professional scientists and engineers. Their lab notebooks are permanent legal records of all work conducted in the laboratory. Because of their importance, professional lab notebooks should be:

• Logs or journals of all the information collected during lab, including procedures and sketches of instruments or tools.
• Written in ink with corrections initialed and noted.
• Labeled with page numbers, time, date, and titles for all procedures, tables, charts, graphs, etc.

Sources of Uncertainty:

In science, a source of uncertainty is anything that occurs in the laboratory that could lead to uncertainty in your results. Sources of uncertainty can occur at any point in the lab, from setting up the lab to analyzing data, and they can vary from lab to lab. This is why it is so important to keep detailed notes of everything you do in the lab procedure and any problems you encounter. Try to be especially aware of any problems in setting up the lab, calibrating instruments, and taking measurements as well as problems with the materials you are using.

For advanced labs, you may want to classify the kinds of uncertainty you have identified. Sources of uncertainty can be classified as random-those that cannot be predicted-or as systematic-those that are related to personal uncertainty, procedural uncertainty, or instrumental uncertainty.

2. Getting ready to collect data:

Before you start collecting data, you need to reconsider the whole point of the lab procedure: to determine whether or not your hypothesis is supported by the data from the experiment. Revisiting your hypothesis and gathering information about the data you will be collecting will help you to better understand your data as you are collecting them. It will also help you to organize your data in a table or spreadsheet.

• Review and restate the hypothesis you are testing and the variables involved. This may be a good time to refer to your PreLab. If you haven't completed a PreLab, create a hypothesis now before you start the lab procedure.
• List the variables in the experiment, noting which are independent and which are dependent. Refer to your PreLab if you have completed it.
• Next to each variable, write the units of measurement you will use in the lab. Noting the unit of measurement for each variable will help you to be sure you are recording the data correctly.
• Determine whether or not you have control and treatment groups in this experiment. Determining whether or not your experiment uses control and treatment groups will help you to structure your data so that you can see more clearly the relationship between those two groups.

(See below for definitions of underlined words.)

Hypothesis:

A hypothesis is scientist's best estimation, based on scientific knowledge and assumptions, of the results of an experiment; it describes the relationship between the dependent and independent variables. Since dependent variables "depend" on independent variables, there has to be a relationship between the two. The anticipated relationship between the dependent and independent variables is the result you expect when one variable reacts with another. In science, relationships between variables are usually shown in graphs. The independent variable is plotted along the horizontal or x-axis and the dependent variable along the vertical y-axis.

Variables:

A variable is what is measured or manipulated in an experiment. Variables provide the means by which scientists structure their observations. Identifying the variables in an experiment provides a solid understanding of the experiment and what the key findings in the experiment are going to be.

To identify the variables, read the lab procedure described in the lab manual. Determine what you will be measuring and what you will be manipulating for each measurement. The first of these are the dependent variables and the other is the independent variable (see definitions and examples below). Write down the dependent and independent variables.

A dependent variable is what you measure in the experiment and what is affected during the experiment. The dependent variable responds to the independent variable. It is called dependent because it "depends" on the independent variable. In a scientific experiment, you cannot have a dependent variable without an independent variable.

An independent variable is the variable you have control over, what you can choose and manipulate. It is usually what you think will affect the dependent variable. In some cases, you may not be able to manipulate the independent variable. It may be something that is already there and is fixed, something you would like to evaluate with respect to how it affects something else, the dependent variable.

It is possible to have experiments in which you have multiple variables. There may be more than one dependent variable and/or independent variable. Usually, you choose one independent variable at a time and observe its effect on one or more dependent variables.

Unit of Measurement:

A standard of basic quantity or increment by which something is divided, counted, or described, such as ml, kg, mm, m/s, °F, etc.

Control and Treatment Groups:

A control group is used as a baseline measure. The control group is identical to all other items or subjects that you are examining with the exception that it does not receive the treatment or the experimental manipulation that the treatment group receives. For example, when examining test tubes for catalytic reactions of enzymes when added to a specific substrate, the control test tube would be identical to all other test tubes with the exception of lacking the enzyme. The treatment group is the item or subject that is manipulated. In our example, all other test tubes containing enzyme would be part of the treatment group.

3. Preparing a table or spreadsheet for recording your data:

Using the information you have gathered about the data you will be collecting, create a raw data table or set up a spreadsheet (refer to the web version of this document to access these resources) for entering your data. (If your lab manual already has a table for the data, skip this step.)

For help in determining which you should create now, a table or a spreadsheet, see below for a comparison of the two. For general information on tables go to "Graphing Resources" in the Resources page on the web version of this document. Choose "Designing Tables."

Creating a Table or a Spreadsheet:

A table provides a very convenient tool for organizing the data you collect in your lab. You can quickly draw a table on a sheet of paper, you can make one with a word processing program, or you can generate one with spreadsheet software. Using a hand-drawn table in the lab also allows you the flexibility of entering the data into a spreadsheet at a later time. The chief advantage to entering data in a spreadsheet is that you can easily convert it not only into a table but also into all sorts of graphs.

Use this guide to figure out whether or not you should use a table or a spreadsheet for recording your data in the lab:

• If you do not have access to a computer with spreadsheet software in your lab, then you should create a table. You can use the data in the table to generate a spreadsheet later, if necessary.
• If you know you will need to create graphs for your data and have access to spreadsheet software in the lab, then use the spreadsheet.
• If you are not sure what form, table or graph, you will be using to report your findings and it is convenient to use a spreadsheet, then use a spreadsheet.
• If creating a spreadsheet in the lab will take too much lab time, then use a table and create the spreadsheet later.
  
  

4. Conducting the experiment:

Carefully follow the experimental protocol. As you conduct your experiment and record your data, take notes on what you are doing and on any changes in your procedure. Also, describe in writing or sketch out on a sheet of paper your observations as you collect data during the experiment (observations are potentially significant things that are not reflected in the measurements: color, smell, interesting reactions, unexpected behaviors, etc.) As you record your data, take note of any trends emerging in the data.

Taking good notes will help you recall the experiment later on when you are writing your lab report. It's also important to note any problems with the procedure or deviations from the established protocol. Even if you are following the protocol in a lab manual, sometimes you will set up and run things differently.

As you record your data, you should be asking yourself various questions: What are the relationships among the variables? Do the data behave in the way that you had anticipated? If not, why not? If the data make no sense, you may need to consider sources of uncertainty once again. Sources of uncertainty may affect the accuracy and precision of your experimental data. For more information on statistical calculations and graphical display of uncertainty, see the graphing tutorial on Using Error Bars in Graphs.

(See below for definitions to underlined terms.)

Relationships Among the Variables:

Since dependent variables "depend" on independent variables, there has to be a relationship between the two. The relationships between the dependent and independent variables are what is described in the hypothesis. So it's important to determine what those relationships are in order to see whether or not the hypothesis has been supported.

Sources of Uncertainty:

In science, a source of uncertainty is anything that occurs in the laboratory that could lead to uncertainty in your results. Sources of uncertainty can occur at any point in the lab, from setting up the lab to analyzing data, and they can vary from lab to lab. This is why it is so important to keep detailed notes of everything you do in the lab procedure and any problems you encounter. Try to be especially aware of any problems in setting up the lab, calibrating instruments, and taking measurements as well as problems with the materials you are using.

For advanced labs, you may want to classify the kinds of uncertainty you have identified. Sources of uncertainty can be classified as random-those that cannot be predicted-or as systematic-those that are related to personal uncertainty, procedural uncertainty, or instrumental uncertainty.


Accuracy and Precision:

Accuracy refers to the closeness of a measured value to a standard or known value. For example, if in lab you obtain a weight measurement of 3.2 kg for a given substance, but the actual or known weight is 10 kg, then your measurement is not accurate. In this case, your measurement is not close to the known value.

Precision refers to the closeness of two or more measurements to each other. Using the example above, if you weigh a given substance five times, and get 3.2 kg each time, then your measurement is very precise. Precision is independent of accuracy. You can be very precise but inaccurate, as described above. You can also be accurate but imprecise.

For example, if on average, your measurements for a given substance are close to the known value, but the measurements are far from each other, then you have accuracy without precision.

A good analogy for understanding accuracy and precision is to imagine a basketball player shooting baskets. If the player shoots with accuracy, his aim will always take the ball close to or into the basket. If the player shoots with precision, his aim will always take the ball to the same location which may or may not be close to the basket. A good player will be both accurate and precise by shooting the ball the same way each time and each time making it in the basket.

5. Visualizing the data:

Now that you have entered your data in a table or spreadsheet, you are ready to represent the data in the appropriate visual format for your lab report. Representing your data in a visual format will allow you to identify trends and relationships among variables more easily. Follow these steps:

• Establish what types of data you have, quantitative or qualitative (refer to the Resources page in the web version of this document; once there, choose "Data Types").
• Determine if the data should be represented as a table or a graph (refer to the Resources page in the web version of this document; once there, choose "Tables vs. Graphs").
• If you decide to use a graph to represent your data, determine which type of graph is one that best represents your data (refer to the Resources page in the web version of this document; once there, choose "Graph Types").
• If a table is the best format for your data, then modify the table you used to collect your data so that it is labeled and organized properly (refer to the Resources page in the web version of this document; once there, choose "Designing Tables").
• If you need help creating a spreadsheet to make a table or graph, refer to the Resources page in the web version of this document. Once there, choose "Excel Tutorial".
• Remember that the purpose of your table or graph is to summarize your findings for yourself and for others and to reveal trends in your data.
  

6. Making sense of your data:

Review all your data--tables, graphs, and drawings--and try to make sense of the overall findings of the lab procedure. Summarize the overall findings in a sentence or two. If your lab instructor says it is permissible, compare your findings with those of other students in the lab.

Summarizing your data in a sentence or two helps you to understand the lab. It is also useful for when you write the Results section of your lab report.

Corroborating data or sharing findings is a very common practice among scientists, which usually leads to more ideas and experimentation. For this reason, comparing your results to other students' results can be valuable as a way of testing your findings. It's OK if your findings are different. Your job is to try to figure out why, to identify the sources of the difference. You can use this information when explaining your findings in the Discussion section of your lab report.