Lesson Plan – week of November 8, 2010
Monday: – no class (speaker)
Tuesday:
Review: importance of research and developing a research question, hypothesis
Discuss:
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Steps
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Identify questions of interest
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Formulating an explanation
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Theory: broad explanation
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Hypothesis: prediction stated in a way that it can be tested
Carrying out research designed to support or refute
Who participates in the study?
Representative sample
How do psychologists study behavior?
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Descriptive studies – recording of behaviors that have been recorded systematically
o Simplest method of scientific inquiry
o Describe behavior and mental processes
o Most widely used
o Survey method – ask people’s opinions
 Case study – one individual
 Naturalistic observation – watch, describe
 Archival research – using already collected data - newspapers
 Clinical method – observe in clinic setting
All have advantages and disadvantages
Correlational Studies
– Correlational method: measure two variables for statistical relationship
– Variable: anything that can be assigned a numerical value
– Uses quantitative measures
Correlational Studies
– Correlation coefficient
• Measures each variable
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Indicates strength ( - 1 to 0 to 1) and direction (negative or positive) of
relationship
Correlation does not mean causation – could be a third factor involved
• Positive correlation – both factors increase
• more study, better grades
• Negative correlation – as one factor increases, the second factor decreases
• More study, less recreation
• No relationship (close to zero) – number of hours studied and height
CORRELATION IS NOT CAUSATION
• Lack of interest could be affecting test performance not hours studied
Wednesday:
Experimental research:
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Tests relationship of two or more variables
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Allows conclusions about cause-and-effect
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Quantitative measures of behavior compared in different conditions created by
researchers
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Evidence supports or rejects hypothesis
Elements
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Independent variable – gets manipulated
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Dependent variable – amount of change
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Experimental group – exposed to independent variable or conditions expected to create
change
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Control group – presents normal behavior used for comparison
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Random assignment
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Experimental control
Summarize the four types of research and discuss the advantages and disadvantages
Experimental: Manipulation and control of variables
Purpose: identify cause and effect
Advantages:
Allows researchers precise control over variables
Can identify cause and effect
Disadvantages:
Ethical concerns, practical limitations, artificiality of lab condition, uncontrolled variables
confound results, researcher and participant biases
Descriptive Research: naturalistic observation, case studies, surveys
Purpose: observe, collect and record data
Advantages:
Minimizes artificiality, easier to collect data, allows description of behavior and mental
processes as they occur
Disadvantages:
Little or no control over variables,
researcher and participant biases
cannot explain cause and effect
Correlational research: statistical analyses of relationships between variables
Purpose: identify relationships and how well one variable predicts another
Advantages: helps clarify relationships between variables that cannot be examined by other methods
and allows prediction
Disadvantages: researchers cannot identify cause and effect
Biological research: Studies the brain and other parts of the nervous system
Purpose: identify causation as well as description and prediction
Advantages: shares many of the advantages of experimental, descriptive, correlational research
Disadvantages: shares many of the disadvantages of experimental, descriptive, correlational research
Hand out article and worksheet – for Tuesday
Thursday:
Spend period reviewing for exam – go into computer lab and using quizlet.com (a flashcard and study
game website) go over the material for the exam
Friday:
Exam – Units 1-4
Monday: November 15, 2010
Watch video on Intelligence Unit – learner.org
Tuesday, November 16, 2010
Work on article worksheet – read article, fill out answers
Wednesday, November 17, 2010
Discuss experimenter and subject biases:
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Internal validity – the extent to which changes in the dependent variable can be attributed to
the independent variable
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Confounding variable – a variable whose unwanted effect on the dependent variable might be
confused with that of the independent variable
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Subject bias – what the subject expects the study to be about
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Experimenter bias – what the researcher expects
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Experimenter effects – the personality, dress
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Pygmalion effect – the subject performs better because of experimenter
Double blind technique
Types of Random Assignment
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Placebo control
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Placebo effect: provides no active effect
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Use in identical conditions for control and experimental groups
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Blind experiment
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Researchers blind to group membership of participants to rule out experimenter bias
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Strongest experiments – double blind
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Researchers and participants kept blind
Thursday, November 18, 2010
Descriptive statistics – how do we understand the data?
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Central tendency asks what the average score is like in the distribution of scores
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Mean: Statistical average of all scores
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Median: The fiftieth percentile (half of the scores are above this score, half are below)
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Mode: The most frequent score
Variability asks how dispersed the scores are relative to the average score or mean
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Standard deviation: How far the average participant score deviates from the average
(square root of the variance)
Standard score – (z score)
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scores on a normal curve can be described as their distance from the mean of the
distribution using SD units
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It allows you to compare scores from different distributions
Percentile
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The score at or below which a particular percentage of scores fall
Friday, November 19
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Skewness - when scores are bunched up on either side of the bell curve
LOOK AT THE TAIL OF THE SKEW
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Scores bunched at the high end = negative skew
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Test is too easy
Scores bunched at the low end = positive skew
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Test is too hard
Is the difference between the two groups caused by our manipulation or by chance?
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We test the null hypothesis – we predict that there will be no effect of the independent variable
No difference btw the groups – fail to reject the null hypothesis
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Difference between the two groups – reject the null hypothesis
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BUT IS THIS BY CHANCE OR FOR REAL?
We are looking for true difference between groups – a statement of probability
the larger the difference between the groups, the more likely it is not by chance.
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Psychologists accept .05 as being statistically significant
A probability of less than 5% that the results occurred by chance
The results are more likely to be statistically significant if:
Samples are large
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The differences between the two means is large
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The variability within the groups is small
Internal validity – the extent to which changes in the dependent variable can be attributed to
the independent variable rather than a confounding variable
External validity – the extent to which the results of a research study can be generalized
Reliable – safe to generalize from a sample
Representative sample
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More cases are better than fewer
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