Scientific Research. The Scientific Method. Scientific Explanation

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Noel Fowler
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1 Scientific Research The Scientific Method Make systematic observations. Develop a testable explanation. Submit the explanation to empirical test. If explanation fails the test, then Revise the explanation to account for the new finding or Develop a new explanation Repeat the process Scientific Explanation A scientific explanation identifies specific variables and proposes how those variables are related. A variable is a characteristic of something, such as a person s weight. Two variables are said to be related if changes in the value of one variable tend to be systematically accompanied by changes in the value of the other variable. 1

2 Methods for Determining Relationships There are two basic methods for determining relationships between variables: The correlational method The experimental method Each method has its own advantages and disadvantages. The Correlational Method Observe and record the values of two (or more) variables across a number of individuals. Identify any relationships that may exist between the variables. Create a scatter plot of the data and examine it for relationships. Compute the correlations between variables. Scatter Plot Weight Height 2

3 Types of Relationship Direct or positive relationship As X increases, Y increases. Example: Weight goes up with height. Inverse or negative relationship As X increases, Y decreases. Example: As body weight increases, running speed goes down. Pearson r Statistic indicating the direction and magnitude of the relationship between two variables. The sign (+ or -) indicates the direction of the relationship (direct or inverse). The size indicates the magnitude. 0 = no relationship 1 = all points fall on same straight line. Example: +.80 = moderately strong direct (positive) relationship, with most points falling relatively close to the best-fitting straight line. Advantages of the Correlational Method Can be used to screen for naturally occurring relationships. Can be used when doing experiments would be impossible or unethical. Findings are likely to apply more generally than those from controlled experiments. 3

4 Disadvantages of the Correlational Method Used by itself, the correlational method cannot establish whether a relationship is one of cause and effect. Two reasons why not: Directionality Problem is X influencing Y or the other way around? Third Variable Problem are X and Y both being driven by a third variable? The Experimental Method Manipulate the variable you think acts as a cause. This is the independent variable. Observe the variable you think may be affected by the independent variable. This is the dependent variable. Hold all other variables constant. These are the extraneous variables. Advantage of the Experimental Method By manipulating the IV while holding extraneous variables constant, the experimental method makes it possible not only to demonstrate a relationship between the IV and DV, but to prove that the observed relationship is one of cause and effect. 4

5 Disadvantages of the Experimental Method Results may not generalize well to the larger population. Cannot be used where it is either impossible or unethical to expose participants to the conditions of the experiment. Theory Versus Practice In theory, if the dependent variable changes systematically with the independent variable, then the IV has been shown to cause the changes in the DV. In practice, it is rarely possible to hold all extraneous variables constant. So, changes in the DV could be due to variation in one or more extraneous variables. Dealing with Extraneous Variables in Experiments Where possible, extraneous variables are held constant. But variables such as subject characteristics cannot be controlled in this fashion. The solution for these latter variables is to control them using statistical methods. 5

6 Statistical Control of Extraneous Variables Randomly assign participants to groups. Expose each group to a different level of the independent variable. Use inferential statistics to determine the reliability of any differences in the average performances of the groups on the dependent measure. Logic of Inferential Statistics Because of random assignment, groups will tend to be nearly equivalent, on average, in the values of the extraneous variables. If the independent variable has no effect, then any differences in performance must be due to chance differences in these extraneous variables. Logic of Inferential Statistics (continued) Inferential statistic estimates the probability p of observing a difference at least as great as the one actually obtained, assuming that the difference is only a chance difference. If p is small enough, then we say that the difference is statistically significant and conclude that the difference was not a chance difference. Therefore, it must be due to our independent variable. 6

7 Statistical Versus Practical Significance Statistical significance means only that an observed difference was unlikely to have occurred purely by chance. On this evidence, we conclude that it was probably a reliable (reproducible) effect of our independent variable. Practical significance means that the difference was large enough for be useful for some practical purpose. A difference can be statistically significant but so small as to have no practical significance. Confounding Confounding exists when two variables vary in such a way that the effect of one variable cannot be separated from the effect of the other. When results are confounded, they are uninterpretable. 7

04/12/2014. Research Methods in Psychology. Chapter 6: Independent Groups Designs. What is your ideas? Testing

04/12/2014. Research Methods in Psychology. Chapter 6: Independent Groups Designs. What is your ideas? Testing Research Methods in Psychology Chapter 6: Independent Groups Designs 1 Why Psychologists Conduct Experiments? What is your ideas? 2 Why Psychologists Conduct Experiments? Testing Hypotheses derived from