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Outline

Review of descriptive methods Naturalistic observations Advantages and disadvantages Case studies Advantages and disadvantages Surveys/interview Advantages and disadvantages Correlational research Advantages and disadvantages

Overview of experimental research How it differs from descriptive research Manipulation of variables Cause and effect General logic behind experiment Two or more groups On average as similar as possible Manipulation performed on one group Example – Study by Simpson and Clark “Effects of THC (active ingredient in marijuana) on memory

Components of an experiment Independent and dependent variables Variables in our example Control and experimental group How do they differ How are subjects assigned Importance of random assignment

Why is randomization your friend Best way to make it so that ON AVERAGE the control and experimental groups are as similar as possible on any given measure Not a guarantee Not randomizing introduces potential confounds Example: Suppose didn’t randomize in THC study Imagine following data: Average weight of control group =150 lbs Average weight of experimental group = 190 lbs Experimental group remembers 2 items less than control Manipulation of THC confounded with weight

Randomization example

Analyzing results Once data is collected (both descriptive and experimental) need to be analyzed Measures of central tendency Purpose Mean Median Mode Measures of variability Range Standard deviation

Understanding standard deviations On average, how much does each score differ from the mean? First find mean of a set of scores Next subtract each score in the set from the mean Square each difference (gets rid of negative numbers) Add all the squared differences (analogous to computing mean) Divide by 1 less than total number of scores Take the square root of the result

Example Scores on first exam: 10, 40, 90, 50 First find mean (10 + 40 + 90 + 50)/4 = 47.5 Subtract mean from each score then square (10 – 47.5)2 + (40-47.5)2 + (90-47.5)2 + (50-47.5)2 = 3275 3275/3 = 1091.6 Square root of 1091.6 = 33 Standard deviation of the above scores is about 33

Importance of standard deviation Standard deviation tells how variable your data set is When you report a mean MUST MUST report standard deviation The standard deviation tells you how representative the mean is of your data set The effects of outliers on the mean

Deciding whether to curve exam Exam 1:  10, 10, 10, 50; Mean = 20 Exam 2:  10, 20, 25, 25;  Mean = 20 Conclusion?  Because means are the same must either curve both or curve neither. Sorry no curve Standard deviation exam 1 = 20 Standard deviation exam 2 = 7 Relationship between mean and standard deviation

Slide 11

Summary Psychology is a science because relies on scientific method Importance of data collection Descriptive methods of collecting data Naturalistic observations, case studies, interviews, surveys, correlations Experiment as method for gathering data Independent and dependent variables Control and experimental group  Random assignment Data analysis Measures of central tendency Measures of variability

Ethics in research

General ethical guidelines “Do no harm” Principle of informed consent Participation is voluntary No coercion Free to withdraw Compensation is NOT contingent on completion Importance of debriefing

Who enforces the guidelines Institutional review board (IRB) at each University Professional  societies APA, APS Journals Granting agencies NIH, NSF