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Elements of an Experiment: Purpose, Variables, Groups, and Central Tendency

This chapter explores the purpose and elements of an experiment, including the independent and dependent variables, experimental and control groups, the placebo effect, single-blind and double-blind studies, and measures of central tendency.

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Elements of an Experiment: Purpose, Variables, Groups, and Central Tendency

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  1. Chapter 2 Section 4 The Experimental Method Obj: Describe the purpose and elements of an experiment.

  2. The method researchers use to answer questions about cause and effect is the experiment. In an experiment, participants receive what is called a treatment, such as a change in room temperature or a new drug. Researchers then carefully observe the participants to determine how the treatment influences their behavior.

  3. Independent and Dependent Variables Experiments contain variables, which are factors that can vary, or change. In an experiment, the independent variable is the factor that researchers manipulate so that they can determine its effect. A dependent variable depends on something-the independent variable. For example; experiment testing the hypothesis that warm temperatures cause aggression. Temperature is the independent and level of aggression is the dependent.

  4. Experimental and Control Groups Ideal experiments use experimental and control groups. Members of an experimental group receive the treatment. Members of a control group do not. Every effort is made to ensure that all other conditions are held constant for both groups, and people are randomly assigned to both groups. This method makes it possible for researchers to conclude that the experiments results are caused by the treatment, not by something else. This type of experiment is called a controlled experiment.

  5. The Placebo Effect The question of whether psychotherapy works is further complicated by the fact that people who seek psychotherapy usually expect it to work. In research studies and in our daily lives, our expectations affect what happens to us. Feeling better simply because we expect to feel better-and for no other reason-is an example of the placebo effect. A placebo is a substance or treatment that has no effect apart from a person's belief in it.

  6. Single-Blind Studies Expectations can create bias toward certain points of view. One way researchers can avoid the influence of expectations is by keeping participants unaware of, or blind to, the treatment they are receiving. In a single-blind study, participants do not know whether they are in the experimental group or the control group.

  7. Double-Blind Studies Participants may not be the only people involved in an experiment who have expectations. Researchers themselves may also have expectations, such as a belief about the effectiveness of a particular treatment. It is therefore useful if the researchers are also unaware of who has had the treatment and who has had the placebo. A study in which both participants and experimenters are unaware of who receives the treatment is called a double-blind study. This is required by the FDA.

  8. Central Tendency and Dispersion Researchers organize data to generalize about the information. Teachers do this every time they analyze test scores. A common technique is to measure or determine central tendency. When the teacher adds all scores and divides the sum by the number of students who took the test, he or she finds the mean, or average score. The mean is most often used as the central tendency.

  9. Other methods of arriving at the central tendency include finding the median and the mode. If scores are organized from the lowest to the highest, or the highest to the lowest, the median score is the middle score. Half of the grades are below this score and half are above. The mode is the most frequent score.

  10. To understand the distribution or dispersion of data, researchers must document the range or scores, or how variable the scores are. The two most frequently used measures of variability are range and standard deviation. To find the range, the lowest score in the data is subtracted from the highest. This is a simple technique and gives a crude measure of variability. Standard deviation is a measure of distance of every score to the mean. The larger the standard deviation the more spread out the scores are.

  11. If five students got 7 out of 10 questions correct on a test, two students got 10 correct, and one got 5 correct, the mode is 7, the median is 7, and the mean is 7.5. To compute the standard deviation, subtract the mean from each score. 10 minus 7.5 equals 2.5. This is a positive deviation because the score is above the mean. Seven minus 7.5 is negative.5 and 5 minus 7.5 is negative 2.5. Test scores that have a large range have a relatively higher standard deviation while test scores bunched together, as in this case, have a relatively small standard deviation.

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