Introduction to Psychology

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## Introduction to Psychology

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**Introduction to Psychology**Class 5: The Scientific Method 2 June 19, 2006**Measures of Central Tendency**Consider this sample: 3 3 5 6 7 2 8 9 5 5 3 30 Mean = 86/12 = 7.17 Mode = 3 and 5 (bimodal) Median = (5 + 5)/2 = 5 Outlier**Correlation**• Answers the question: what is the linear relationship between two variables • Consider amount of coffee and performance on an exam in a sample of coffee drinkers as an example Number of cups Exam score 1.0 90 1.5 89 2.0 95 2.5 95 3.0 99**Graph**The Correlation between Performance and Amount of Coffee r = +.92**NUMBER VALUE: 0 to 1 and SIGN: + or –**r = + .63 r = + .89 r = + 1.0 r = + .28 r = ~ 0 r = - .91**Limitations**r = - . 18 Works for LINEAR relationships only.**SCORE**COFFEE EXPECTATION Correlation is NOT causation.**Experimentation**Control group Random Assignment Independent variable/s Dependent variable/s Experimental group Statistical tests**Example**• Design an experiment to test the effect of drinking coffee prior to an exam on performance and expectations in agroup of coffee drinkers • ONE independent variable Caffeinated or decaf drink (2 levels) • TWO dependent variables: Actual exam score Expected exam score**Procedure**• Give subjects instructions to not drink any coffee before the experimental session • Randomly assign coffee drinkers to control (n=20) and experimental group (n=20) • Make participants in the control group drink a cup of decaf and those in the experimental group drink a cup of coffee, but tell both that it is coffee • Give them all the same exam under the same conditions • After they finish, ask them to estimate their score on the exam • Then actually score their exams • Compute the means for each variable and group**Results**Actual score Expected score Coffee 85.1 Coffee 90.8 Decaf 75.9 Decaf 91.2 Insignificant difference * Significant difference * * Determined statistically**Design an experiment!**• Group activity • Come up with an experiment that has: 1 independent variable 1 dependent variable • Define your sample • Explain your procedure • State your hypothesis • Present your experiment