ap psych prep 2 (part ii) - more methods, statistics
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AP Psych. Prep. 2
Part II: More
ResearchMethods,Statistics
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Other Research Methods
The experimental method can be veryvaluable because it can show us theCAUSE if we are very careful in ourdesign.
But sometimes experiments areimpossible, or not well matched to the
topic or level of detail we are studying.
So we have a few other methods we canuse
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Correlational Method
Correlation a measure of therelationship between two variables. (nomanipulation, so no real I.V.)
Sometimes we cant assign participants togroups (e.g. boys and girls).
NOTE: if we do an experiment with pre-made groups like this, its called pseudo-experiment or ex post facto study.
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Correlational Method
Or sometimes its unethical to assignparticipants to groups. E.g. smokers vs.not smokers, victims of violence vs. notvictims
Correlational method involves measuringtwo variables, and calculating a correlation
coefficient, which is a number that tells usabout the strength and direction of therelationship between the them. (Seestatistics below)
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Survey Method
NOTE: Survey Method vs. Survey tool -We can use surveys as a tool in othertypes of methods (e.g. experimental).
Survey METHOD a type of correlationalmethod where you use give participants asurvey and then correlate variables to find
relationships.
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Survey Method
Survey method can be very easy andcheap to do.
But some negatives to this method: Confounding variables
Random sampling is difficult
Low response rate
People can lie
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Statistics (stats)
We use statistics to describe and makedecisions when we do scientific research.
1. Descriptive statistics stats thatdescribe a set of data.
1A. Frequency Distribution grouping
participants by some characteristic (e.g.what kind of phone do people own)
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We can Graph frequency distributions
Histogram (bar graph):FrequencyPolygon:
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1B. Measures of Central Tendency
MofCT try to mark the center of adistribution of numbers.
Mean average of the numbers
Median central score of orderednumbers; if odd number of values, halfway between middle numbers
Mode the most common number; canhave morethan one mode (bimodal, etc)
E.g. 6, 7, 7, 8, 8, 9, 9, 9, 10
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Outliers and Skewed Distributions: One or more veryhigh or very low scores will skew a distribution. Canbe skewed with a right tail (positive or right skew)
or left tail (negative or left skew)
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1C. Measures of Variability
Measures of Variability try to show howspread out a distribution is.
Measures of Central Tendency cant tell usabout thesedifferent shapes.
E.g.
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1C. Measures of Variability
Range the distance between the highestand lowest numbers
Variance and Standard Deviation twomeasures of the average distancebetween the data points and the mean(average)
Standard Deviation = Variance
High # = more spread out
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Normal Curve / Normal Distribution
Closely connected to measures ofvariance.
Normal Curve special bell-shaped curvewith certain number of scores within
different ranges.
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Normal Curve / Normal Distribution
1 S.D.= zscore of1
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Normal Curve / Normal Distribution
If your z-score on a test is +2, what
percentage of competitors did you do scorebetter than?
____________________________________
If the standard deviation is 25, and the meanis 100, what number will be at z score -3?____________________________________
What is the z score below which the lowest 16percent of people will score?____________________________________
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Correlation Coefficient
Correlation coefficient number thatmeasures the relationship between twovariables.
Can be positive or negative. Positivemeans when one variable increases, sodoes the other. Negative means when onegoes up, the other goes down.
A score of 0 means theres no relationship.
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Value of the correlation coefficient indicates howstrong the connection between the variables is.Closer to -1 or +1 are strong, farther are weaker.
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Correlation Coefficient
Important Notes:
CORRELATION does NOT equalCAUSATION.
Even if we find a perfect -1 or +1correlation between two variables, we CANNOT tell anything about the cause of therelationship.
** Shark Attacks and Ice Cream Sales **
Also, strong correlation positive
correlation
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2. Inferential Statistics
Inferential Stats help us decide if thedifferences we see in our numbers are realdifferences between our experimental andcontrol groups, and if we should
generalize our results to the widerpopulation.
Helps us answer: Is our result due tosampling error? Due to chance? Due tosmall sampling size?
Or is it because of a real difference?
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2. Inferential Statistics
Larger sample size, and larger differencebetween the exp. and control groupsmake it more likely we will find a stat.significant result
Many tests that do this. Two examples: T-tests
ANOVA (Analysis of Variance)
These tests give us a pvalue.
Smaller pvalue = less likely due tochance
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2. Inferential Statistics
Scientists generally agree that a pvalue of.05 or less means we have a statisticallysignificant result. (A real differencebetween our groups)
p= .05 means that only 5% of the timeour result is due to chance. I.e. one timeout of 20 trials.
We can also make p values for correlationcoefficients; see if our sample size waslarge enough, how sure we can be thatour result is real, etc.
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2. Inferential Statistics
We are never 100% sure, but if we arevery careful in our experiment design, andtest multiple times and find low pvalues,we start to feel confident that we are
seeing a real explanation, a real cause.
Question: What do we think if we get a pscore of .10 ? __________________
Of .055 ? __________________
Of .005? __________________
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Research Ethics
Also very important.
APA sets ethical guidelinesfor all psych research.
All studies must be approved by
Institutional Review Boards (IRB) Submit proposal of procedure and ethical
protections, and IRB will approve or deny
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Research Ethics - Animals Must have scientific purpose
Must answer an important question Animals must be best for the question
Must care for and house animals
humanely Get animals legally, from approved
sources
If you MUST use wild animals, catch in a
safe and humane way Study must employ the absolute
LEAST amount of suffering possible
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Research Ethics - Humans
Must be voluntary - cant force or coercepeople to participate
Informed Consent person must
understand and agree to participate.Sometimes we can deceive a little bit (ifwe need to) but we need to be verycareful.
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Research Ethics - Humans
Anonymity / Confidentiality protectidentity and personal information.
Anonymity name and data cant be
connected Confidentiality canbe connected, but
promise not to identity the person
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Research Ethics - Humans
Risk cant put participants in a lot ofrisk. Long term mental or physical harm isnot allowed.
Temporary stress or discomfort isallowed,if its necessary for the specific question.E.g. ice pain studies
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Research Ethics - Humans
Debriefing after study, must explainstudy and give ways to contact researcherlater. Offer to give results to participantswhen study is over.
If deception was used, must reveal andexplain why you needed to do it that way.
Some studies we talk about would not beallowed by IRBs today. Stronger ethicalguidelines