Please read the lab handout (See link above).  You can read it online or you can print out a copy, mark it up and bring it lab with you.  I will always have handouts for you when you come to lab.

You will also need  to review some text material for this pre-lab (From Environmental Science by Miller, 2008) These sections can be downloded from the Moodle site for the lab course:

1) section 2-1 on the scientific method
2) sections 15-1 on air pollution

a) Hypothesis driven science

Please read chapter 2-1 in Miller 2008 (See Moodle Site for .pdf download).

Scientists seek to gain new knowledge about the world and universe in which we live.  They do this by constantly asking questions about something they are interested in and then obtain information through observation and experiments to attempt to answer these question.  A hypothesis is a carefully constructed statement that then can be tested.  A null hypothesis is a specific way to phrase a hypothesis statement that compares two populations and is often simple to prove or reject with statistics. 

An example:  I am hiking along the Park River in Hartford and I come across a section of river that contains a pipe that empties into the river.  This is what is known as a point source discharge. I am curious about the water quality above and below the pipe.  A very general hypothesis that I could state could be:  The point source discharge is significantly affecting the water quality of the Park River. Well, that statement could take months ore even years to prove or reject and may be imbedded with multiple complex scenarios.  This hypothesis may be our ultimate goal but we can break it down into more manageable smaller hypotheses that we will state in a specific way. -

Let's start by saying - THERE IS NO SIGNIFICANT DIFFERENCE between the pH value of the river water above the pipe and below the pipe. 

The above hypothesis is a null hypothesis because it assumes no difference between two things.  Often scientists looks for differences in nature so this is usually an easy hypothesis to reject.  If we are able to reject a hypothesis then we have gained some new knowledge.  In our example above we can take pH measurements in the field above and below the pipe, perhaps over the course of a semester.  The two sets of data (pH values above the pipe and the pH values below the pipe) can be analyzed statistically to determine if they differ (more on these statistics below).  If they do differ statistically, then we can reject our null hypothesis and chalk up one piece of evidence for our larger scope hypothesis that states the point source discharge is affecting the water quality of the Park River.  We would then perform additional experiments that would help answer our ultimate question.

b) Vehicle Data Collection - Physical characteristics and Emissions

You will be asked to state testable null hypotheses to examine two populations (parking lots) of vehicles on campus.  One hypothesis will be a physical difference.  In each lot you will collect data on type, make, model and color. Type of vehicle includes: sedan, pick-up, SUV, etc. Make would be the manufacturer - Ford, Acura, Toyota.  Model refers to specific cars - Mustang, Integra, 4-Runner.  An example of a simple null hypothesis about a physical difference would be:  There is no difference between the number of red SUVs in the Ferris lot and the Life Science Lot.  We can count up the number of red SUVs in each lot and then see if our null hypothesis is correct or not.

The second  hypothesis will focus on emission data for the vehicles that you sampled. Begin by reading 15-1 in Miller (See Moodle site for lab).  Next, browse the website listed below.  You will refer back to this site after you have collected your vehicle data.  You will also need to use the information from Miller 15-1 and this sites to answer some of the pre-lab questions.

Fueleconomy.gov  http://www.fueleconomy.gov/

After you browse this site it will be easier to formulate null hypotheses that focus on vehicle emissions.  You will be asked to choose two parking lots on campus to compare.  Make note that there are some lots that are designated for faculty and some that are designated for students.  These designations could make for some interesting comparisons.  Due to construction projects, some lots may not currently have cars on them. Click here for the current campus map.

 Once you have collected vehicle data you can perform some simple statistical tests to determine if your values from the two populations are  significantly different from one another.  The t-test can be run in Microsoft Excel to obtain these results.  For many of us statistics are a bit scary (including me!).  I have found a website from Jim Deacon ant the University of Edinburgh that explains the basics of statistics with some examples using methods by hand and Microsoft Excel.  click here.  We will go over the t-test in lab but make sure you are familiar with basic descriptive statistics such as mean, standard deviation and variance.

If you are not a wiz with Microsoft Excel yet.....don't worry you will be by the end of the semester. It may well be the most important skill you learn from this class.