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Lesson 2-05 Controls and Experimental Error

Page history last edited by Julie McShea 11 years, 8 months ago


Opened 10/15 due by 10/19 



LESSON 2.05 – Controls & Experimental Error

Standard:  IE1.b, c, j




In this lesson you will learn about how experiments are set up to test a hypothesis and how sometimes an error can happen.



1.    Read the following (you will be taking Cornell notes and turning them in; use the form):




A scientific experiment must have the following features:

·         a control, so variables that could affect the outcome are reduced

·         the variable being tested reflects the phenomenon being studied

·         the variable can be measured accurately, to avoid experimental error

·         The experiment must be reproducible.



An experiment is a test that is used to eliminate one or more of the possible hypotheses until one hypothesis remains. The experiment is a cornerstone in the scientific approach to gaining deeper knowledge about the physical world. Scientists use the principles of their hypothesis to make predictions, and then test them to see if their predictions are confirmed or rejected.



Scientific experiments involve controls, or subjects that are not tested during the investigation. In this way, a scientist limits the factors, or variables that can cause the results of an investigation to differ. A variable is a factor that can change over the course of an experiment. Independent variables are factors whose values are controlled by the experimenter to determine its relationship to an observed phenomenon (the dependent variable). Dependent variables change in response to the independent variable. Controlled variables are also important to identify in experiments. They are the variables that are kept constant to prevent them from influencing the effect of the independent variable on the dependent variable.



For example, if you were to measure the effect that different amounts of fertilizer have on plant growth, the independent variable would be the amount of fertilizer used (the changing factor of the experiment). The dependent variables would be the growth in height and/or mass of the plant (the factors that are influenced in the experiment). The controlled variables include the type of plant, the type of fertilizer, the amount of sunlight the plant gets, the size of the pots you use. The controlled variables are controlled by you; otherwise they would influence the dependent variable.



In summary:

·         The independent variable answers the question "What do I change?"

·         The dependent variables answer the question "What do I observe?"

·         The controlled variables answer the question "What do I keep the same?"



Experimental Design



Controlled Experiments

In an old joke, a person claims that they are snapping their fingers "to keep tigers away," and justifies their behavior by saying "see, it works!" While this experiment does not falsify the hypothesis "snapping your fingers keeps tigers away," it does not support the hypothesis either, because not snapping your fingers will also keep tigers away. It also follows that not snapping your fingers will not cause tigers to suddenly appear.

File:Siberian Tiger by Malene Th.jpg

Figure 7: Are tigers really scared of snapping fingers, or is it more likely they are just not found in your neighborhood? Considering which of the hypotheses is more likely to be true can help you arrive at a valid answer. This principle, called Occam’s razor states that the explanation for a phenomenon should make as few assumptions as possible. In this case, the hypothesis “there are no tigers in my neighborhood to begin with” is more likely, because it makes the least number of assumptions about the situation.

(Source: http://en.wikibooks.org/wiki/Image:Siberian_Tiger_by_Malene_Th.jpg, Photo by: Malene Thyssen, License: GFDL)



To demonstrate a cause and effect hypothesis, an experiment must often show that, for example, a phenomenon occurs after a certain treatment is given to a subject, and that the phenomenon does not occur in the absence of the treatment.



One way of finding this out is to perform a controlled experiment. In a controlled experiment, two identical experiments are carried out side-by-side. In one of the experiments the independent variable being tested is used, in the other experiment, the control, or the independent variable is not used.



A controlled experiment generally compares the results obtained from an experimental sample against a control sample. The control sample is almost identical to the experimental sample except for the one variable whose effect is being tested. A good example would be a drug trial. The sample or group receiving the drug would be the experimental group, and the group receiving the placebo would be the control. A placebo is a form of medicine that does not contain the drug that is being tested.



Controlled experiments can be conducted when it is difficult to exactly control all the conditions in an experiment. In this case, the experiment begins by creating two or more sample groups that are similar in as many ways as possible, which means that both groups should respond in the same way if given the same treatment.



Once the groups have been formed, the experimenter tries to treat them identically except for the one variable that he or she wants to study (the independent variable). Usually neither the patients nor the doctor know which group receives the real drug, which serves to isolate the effects of the drug and allow the researchers to be sure the drug does work, and that the effects seen in the patients are not due to the patients believing they are getting better. This type of experiment is called a double blind experiment.


Controlled experiments can be carried out on many things other than people; some are even carried out in space! The wheat plants in Figure 8 are being grown in the International Space Station to study the effects of microgravity on plant growth. Researchers hope that one day enough plants could be grown during spaceflight to feed hungry astronauts and cosmonauts. The investigation also measured the amount of oxygen the plants can produce in the hope that plants could become a cheap and effective way to provide oxygen during space travel.



Figure 8: Spaceflight participant Anousheh Ansari holds a miniature wheat plant grown in the Zvezda Service Module of the International Space Station.

(Source: http://commons.wikimedia.org/wiki/Image:Anousheh_Ansari_in_the_ISS.jpg, Image by: NASA, License: Public Domain)



Experiments without Controls



The term experiment usually means a controlled experiment, but sometimes controlled experiments are difficult or impossible to do. In this case researchers carry out natural experiments. When scientists conduct a study in nature instead of the more controlled environment of a lab setting, they cannot control variables such as sunlight, temperature, or moisture. Natural experiments therefore depend on the scientist’s observations of the system under study rather than controlling just one or a few variables as happens in controlled experiments.



For a natural experiment, researchers attempt to collect data in such a way that the effects of all the variables can be determined, and where the effects of the variation remain fairly constant so that the effects of other factors can be determined. Natural experiments are a common research tool in areas of study where controlled experiments are difficult to carry out.



Examples include: astronomy -the study of stars, planets, comets, galaxies and phenomena that originate outside Earth's atmosphere, paleontology - the study of prehistoric life forms through the examination of fossils, and meteorology - the study of Earth’s atmosphere.



In astronomy it is impossible, when testing the hypothesis "suns are collapsed clouds of hydrogen", to start out with a giant cloud of hydrogen, and then carry out the experiment of waiting a few billion years for it to form a sun. However, by observing various clouds of hydrogen in various states of collapse, and other phenomena related to the hypothesis, such as the nebula shown in Figure 9, researchers can collect data they need to support (or maybe falsify) the hypothesis.



An early example of this type of experiment was the first verification in the 1600s that light does not travel from place to place instantaneously, but instead has a speed that can be measured. Observation of the appearance of the moons of Jupiter was slightly delayed when Jupiter was farther from Earth, as opposed to when Jupiter was closer to Earth. This phenomenon was used to demonstrate that the difference in the time of appearance of the moons was consistent with a measurable speed of light.




Figure 9: The Helix nebula, located about 700 light-years away in the constellation Aquarius, belongs to a class of objects called planetary nebulae. Planetary nebulae are the remains of stars that once looked a lot like our sun. When sun-like stars die, they puff out their outer gaseous layers. These layers are heated by the hot core of the dead star, called a white dwarf, and shine with infrared and visible colors. Scientists can study the birth and death of stars by analyzing the types of light that are emitted from nebulae.

(Source: http://commons.wikimedia.org/wiki/Image:169141main_piaa09178.jpg, License: NASA/JPL-Caltech/Univ. of Ariz, Public Domain)



Experimental Error

When you make any kind of measurement (mass, volume, distance), you cannot be sure how close you are to the true value of the measurement or how accurate your measurement is.  There is always some experimental error is every measurement.  

Some error results from the measuring apparatus.  Using better tools will result in a better or more accurate measurement.  A digital scale that measures to .01 grams will be more accurate than a bathroom scale measuring to the pound.

Some error will result from the person making the measurements.  Being careful when you measure will give repeatable results.  If after making 3 (or more) measurements of an item, the results are nearly identical, you may be consider your measurement to be precise.  The more measurements you make, the more precise your data will be.  Personal error or errors due to the way the experiment is designed can be minimized.

Note that you may make some measurements that are precise but not accurate and you can also make an accurate measurement within data that is not precise.  You should strive to be both accurate and precise.




1.    Create a Cornell notes document:  2.05-Notes-yourlastname.doc

2.    Take notes on what you have read above.

3.    Turn-in a copy of your notes to the drop-box for this course.





Study your notes.

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