Download The Scientific Attitude

CHAPTER 1 LECTURE NOTES
The Scientific Attitude
 Prepares us to think smarter
 Scientific approach: skeptical but open-minded, humble
 Shifts away from illusions to reality, we must use smart thinking or critical thinking:
thinking that does not blindly accept things, but approaches with skepticism and
examines the evidence carefully:
How did they know, on guts and instinct? Are the evidence biased?

remember, extreme humility = stubbornness

critical thinking:
examines assumptions
discerns hidden value
evaluates evidence
assesses conclusions
The Limits of Intuition and Common Sense
 Intuition often ends up nowhere
 Hindsight bias: tendency to believe that one would have known it after the results are in.
“I knew it all along!”
 Humans tend to be overconfident. We think we know more than we actually do (probably
result of self-serving bias)
o Hindsight causes us to be overconfident as we believe we would have picked the
answer when the results are in front of us.
 False Consensus Effect: tendency to overestimate others’ agreement with us. E.g.
Vegetarians believe larger % of population is vegetarian than carnivores.
 Illusory Correlation: perceiving correlation when non exists. Notice random coincidences as
not random. E.g. As soon as couples stop trying to unsuccessfully conceive and adopt a baby,
a year or two later, they conceive and have a child together.
The Scientific Method
 Scientific theory: explanation using set of principles to organize/predict observations
 No matter how good theory sounds, must put it to test
 Must imply testable prediction = hypothesis
 Beware of bias when testing
 Good experiments can be replicated: experiment can be repeated and would yield constant
results: done with a different group of people
Types of Research
 Case study: research method where one person is studied in depth to find universal principles
(things that apply to all)
o Drawback: that the individual being studied could be atypical, results not universally
contained
 Survey: research method to get the self-reported attitudes/behaviors of people
o Drawback: looks at cases in less depth and wording of questions affects the response
given (framing) We tend to hang around group similar to us so using them as study is
wrong
 Naturalistic Observation: observing and recording behavior in natural settings without any
control of the situation
o Like case study & survey, naturalistic observation does not explain behavior
 Correlation: the way two factors vary and how well one factor may show a relationship to the
other
o positive correlation: direct relationship where factors increase or
decrease together.

Self-esteem
grades
= Positive correlation

Study time
grades
= Positive correlation
o Negative correlation: inverse relationship where one factor increases while the other
decreases

Party every night
grades
OR
Alcohol intake
self-esteem
CORRELATION DOES NOT PROVE CAUSATION,
IT SIMPLY SHOWS A RELATIONSHIP (+ OR -) BETWEEN TWO FACTORS
Experiments
o To isolate cause & effect … to prove causation
o Population: all the cases in the group being studied (all students at ANA with ADHD
not receiving medication)
o Random sampling: sample that gives each member of population a 50-50 chance of
being selected .. to ensure results within range
o Random assignment: assigning subjects from random sampling group to
experimental or control groups to ensure no bias.
o Experimental condition: condition that exposes subject to treatment (given pill to
lessen effects of ADHD)
o Control condition: serves as a static comparison to observe effects of treatment on
experimental condition subjects; subjects not exposed to treatment (given placebo pill
… no effect on ADHD)
o Independent variable: experimental factor being manipulated and studies (pill that
lessens ADHD)
o Dependent variable: factor that depends on manipulation of independent variable
(placebo pill)
o Placebo: inert substance/condition that may be administered instead of an actual
active agent
o Double blind procedure: procedure in which neither the experimenter nor the
subjects know which group is given treatment and which is not
Chapter 1 (addendum): Statistics
 Percentile Rank: percentage that describes your rank among those also being evaluated. (If
your percentile rank on a test is 90, then your score is higher than 90% of the class.) It is
impossible to get 100% percentile rank because you cannot get higher than everyone in the
class, including yourself.
 Mean: average score ….. add all the numbers up and divide by number of items. (The mean
of {2,2,3,10, 98} is 23.)
 Median: middle point of all the items such that half is above the number and half is below the
number (50th percentile). Arrange numbers from highest to lowest or vice versa and find the
number in the middle. (The median of {2,2,3,10, 98} is 3.)
 Mode: number that occurs the most. (The mode of {2,2,3,10, 98} is 2)
 Range: range of the scores is the difference between the highest number and the lowest
number. (The range of a GPA score is from 0.0 to – 4.0
 Standard Deviation: measurement of how far scores differ/deviate from the mean (average).
o The standard deviation of {5,6,5,6,6,7,5,4} is very low because all the items barely
deviate from the mean of 5.5.
o Whereas, the standard deviation of {5,10,8,18,-6.5,-7.22} is high.
Find the Standard Deviation of {2,3,3,4}
1.) Find the mean
(2+3+3+4)/4 = 3
2.) Subtract the mean from each term and
square it.
(2-3)2 = 1, (3-3) 2 = 0, (3-3) 2 = 0, (43)2 = 1
3.) Find the average of the deviations from the
mean.
(1+0+0+1)/4 = 0.5
4.) Square root the average and that is the
standard deviation
0.5 = 0.7071
Normally, this number would be
rounded to the same decimal place
as the data, but 0.7071 is shown for
clearer understanding.
(0.7071 = 1)
 Normal curve: (bell curve) a distribution graph that dictates 68% of the scores should circa
the mean. More specifically, 68% of the scores should fall within 1 standard deviation and 95%
should fall within 2 standard deviations from the mean.
 Scatterplot: graphical representation of data by using dots. The degree of cluster or
formation of a slope can dictate the correlation between two variables.
 Correlation: relationship between 2 events. (Traffic accidents increase with increasing
temperatures; business earnings drop as Christmas ends.)
o Correlation Coefficient: A proportional number that measures correlation - how
strongly two events vary

Positive Correlation: two events increase and/or decrease together.
(increasing study time positively correlates with increasing grades; or decreased
food consumption positively correlates with decreased weight.)


Positive correlation coefficients are positive numbers ranging from 0.00
(no correlation) to 1.00 (perfect correlation). In a scatterplot graph, a
positive correlation exists if a positive slope is seen
Negative Correlation: one event increases and the other decreases or vice
versa. (decreasing number of hours of sleep negatively correlates with
increases in traffic accidents; or increasing alcohol consumption decreases
alertness.) negative correlation coefficients are negative numbers ranging from 1.00 (perfect correlation) to 0.00 (no correlation). In a scatterplot, negative
correlation exists if a negative slope is seen
 Be sure to remember that CORRELATIONS DO NOT NECESSARILY MEAN CAUSATION.
>>> If car accidents increase with increasing temperatures, it does not necessarily mean that
hot temperatures cause more traffic accidents!!
 Be aware of ILLUSORY CORRELATION: seeing relationships between something when
there is none.
>>>If you believe that black-colored dogs are more aggressive than white-colored dogs,
then you will be more likely to notice and recall events where black-colored dogs show
aggressiveness to confirm your belief (also know as "self -serving bias."
 Regression toward the mean: tendency for extreme values to go back ("regress") to the
average value (mean).
>>>If you normally get 80% on your tests and suddenly you got an extreme (unusual) score of
50%, then on your next test you are likely to get around 80% again.
 Statistical Significance: measure of how likely an event is due to chance alone.
>>> If average marks concerning two classes are statistically significant, then the marks are
actually different, not due to random chance or sampling errors.
>>> Statistical significance is usually determined by mathematical analysis of the samples.
GRAPHS (Be Aware Of)



Perfect positive correlation (+1.00)
No relationship (0.00)
Perfect Negative Correlation (-1.00)
F
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q
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n
c
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Symmetrical Distribution
(Bell Curve)
Negatively Skewed Distribution
Positively Skewed Distribution