Learn This: You have to know the difference between an Independent and Dependent Variable.

Transcription

1 The Experimental Method: (Independent & Dependent Variables) Why is this Important? As a psychologist, you will read much research and hear many reports. It is crucial that one can distinguish between experimental and non-experimental research. The Big Points: Experimental and nonexperimental research are distinguished by the degree of control that the researcher has over the subjects and conditions in the study. You must distinguish between manipulation and assignment versus observation. An experiment is an investigation in which some variable is manipulated. You have to know what a variable is: A variable is an aspect of the testing condition that can change or take on different characteristics with changes in conditions Learn This: You have to know the difference between an Independent and Dependent Variable. Fancy Defiiniitiions and Examplles: IV - Independent Variable: The Condition or Factor Manipulated or Selected by the Experimenter to Determine Its Effect on the Subject Examples of IVs: Differential Dosage of a Drug Given Control Fever Different Kinds of Psychotherapies for Depression Various Amounts of Sugar Used to Reinforce A Rat For Running a Maze

2 DV - Dependent Variable: A measure taken from the subject that reflects the effects of the independent variable (IV) Examples of DVs that Correspond to Our IVs: Differential Dosage Measure Body Temperature Psychotherapies Given them a test like the Beck Depression Inventory Sugar Number of Trials it Takes the Rat to Learn the Maze The Nuttshellll -- you change tthe IV & measure iitts effffectt on tthe DV.. Images tthatt Wiillll Hellp Nuance: Subject Variiablles as Independent Variiablles There are variables whose effect on a DV that might be of interest to you but that you cannot manipulate. For example, you might be interested in the role that gender plays in the response to TV violence. Thus, you might have a group of children who view a violent cartoon and a group who view, as a control, a nonviolent cartoon (IV - type of cartoon). Then you measure how aggressively the kids act towards a stuffed animal after watching the show (DV). You test boys and girls (IV). The design would have two independent variables: Cartoon and Gender. However, you did not manipulate Gender. You had to take the children with the gender they came with. This is a subject variable. You can't really say that XX versus XY chromosomes that gave you your result. What about culture? Subject variables are not as clear cut in demonstrating causality as many other independent variables. Other Things You Should Know About Variables Conffounded Variiablles:: A confound occurs when you select an IV and another variable varies with it. What then is the cause of the effect on the DV? Exampllee::

3 The Study: The Effects of Race on Guilty/Not Guilty Decisions in Jury Trials for DWI (Drinking While Intoxicated). Your Hypothesis: People will more easily vote to convict people of different races. Method: Set up mock trials with juries and defendants of similar or varying races. Confound: In the USA, unfortunately, income can vary according to race. Perhaps, people vote to convict folks of different incomes. If you just take a random sample of different ethnic groups - you might have a confounded study. See the graphic below.

4 Solution: Make sure all incomes and races are represented in your groups. How tto choose tthe Levells off an Independentt Variiablle:: 1. Cover as much of the range as practical: You never know what may happen in another time frame. Example: Testing vision after dark adaptation. If you only kept people in the dark for 5 minutes and not 15, you would miss the switch from cones to rods. 2. Have enough values tested not to miss any important relationships? Example: The effects of arousal on performance (the Yerkes-Dodson function). Too little arousal leads to a lower level performance.

5 Too much arousal leads to a low level of performance. Middle levels of arousal leads to best performance. 3. Pay attention to the underlying scale of the IV when picking values. For Example: If you want to increase the loudness of a sound to see if it increases arousal (as in a Yerkes-Dodson experiment), you need to know how the logarithmic decibel scale works. Changee iin db Changee iin ssound eeneerrgy 3 db increase Sound energy doubled 10 db decrease Sound energy decreased by factor of db decrease Sound energy decreased by factor of 100 Therefore, when you want to make a sound twice as loud - what do you change (better take that Sensation and Perception class)? Bottttom Liine: You manipulate the Independent Variable (IV) in an experiment in most cases. Sometimes you have to select subjects with appropriate characteristics. You do this because you can't manipulate the factor (ex. Gender). You hope the manipulation of the IV will affect the Dependent Variable (DV). The DV is the variable you measure. You have to watch out when you manipulate the IV for confounds and the ranges of IV values you choose. It's really an easy idea. Change the IV - Measure the DV