1. Thinking Critically with Psychological Science Chapter 1
Psychology 7e in Modules

2. Scientific Method
Psychologists, like all scientists, use the scientific method to construct theories that organize, summarize and simplify observations.
Making observations
Defining a problem
Proposing a hypothesis
Gathering evidence/ testing hypothesis
Publishing results
Theory building
OBJECTIVE 4| Describe how psychological theories guide scientific research.
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3. Hypothesis Expresses a relationship between two variables.
A variable is anything that can vary among participants in a study.
Participating in class leads to better grades than not participating.

4. Theory
A Theory is an explanation that integrates principles and organizes and predicts behavior or events.
For example: low self-esteem contributes to depression.
If we were to observe that depressed people talk about their past, present, and future in a gloomy manner, we may theorize that low-self-esteem contributes to depression.
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5. Research Observations
Research would require us to administer tests of self-esteem and depression. Individuals who score low on a self-esteem test and high on a depression test would confirm our hypothesis.

6. Publishing results –write and publish article
Making observations computer game designers have varying levels of stress
Defining a problem In what ways are high stress and low stress game designers different? High control vs. Low control?
Proposing a hypothesis Game designers who have more control over difficult tasks will report less stress
Gathering evidence/ testing hypothesis (Randomly assign subjects into two groups:
Forced pace (low control) = high stress
Self pace (high control) = low stress
Publishing results –write and publish article
Theory building use the results to create theory that explains having control over a task reduces stress

7. Below is a comparison of different research methods.

8. Experimentation Exploring Cause and Effect Test hypothesis
Type 1 of Research method
Exploring Cause and Effect
Test hypothesis
Has control and experimental groups
Laboratory experiments are good at controlling variables.
Eating too many bananas causes
Constipation
OBJECTIVE 12| Explain how experiments help researchers isolate cause and effect.
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9. To Perform an Experiments
Directly vary a condition you think might affect behavior
Create 2 or more groups of subjects
Should be alike in all ways except the condition varying
Record whether varying condition have a effect on behavior

10. 1. Experimental subjects/objects. A. Experimental group. B
1. Experimental subjects/objects A. Experimental group B. Control group
Variable- any condition that can change or affect the outcome of experiment
Independent variable
Dependent variable
Extraneous Variable

11. Independent Variable Factor manipulated by the experimenter.
Focus of the study.
The cause of the behavior
For example, when examining the effects of breast feeding upon intelligence, breast feeding is the independent variable.
OBJECTIVE 14| Explain the difference between an independent variable and a dependent variable.
If there is a drug in an experiment, the drug is almost always the independent variable.
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12. Dependent Variable Whatever is being measured in the experiment.
It is dependent on the independent variable.
The dependent variable would be the effect of the drug.
For example, in our study on the effect of breast feeding upon intelligence, intelligence is the dependent variable.

13. Beware of Confounding/Extraneous Variables
The object of an experiment is to prove that A causes B.
A confounding variable is anything that could cause change in B, that is not A.
If I wanted to prove that smoking causes heart issues, what are some confounding variables?
Lifestyle and family history may also effect the heart.

14. Single-blind & Double-blind Procedure
Evaluating Therapies
Single-blind & Double-blind Procedure
In evaluating drug therapies, patients and/or experimenter’s assistants should remain unaware of which patients had the real treatment and which patients had the placebo treatment.
OBJECTIVE 13| Explain why random assignment and double-blind procedure build confidence in research findings.
Placebo Effect
Experimenter Effect
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15. Evaluating Therapies Random Assignment
Assigning participants to experimental (Breast-fed) and control (formula-fed) conditions by random assignment minimizes pre-existing differences between the two groups.
Sometime research participants out of enthusiasm or personal beliefs can affect the out come of an experiment. To control for such affects, a double-blind procedure is used, in which the participants and the experimenter’s assistants are not aware of which participants got real treatment and who got placebo.
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16. Hawthorne Effect But even the control group may experience changes.
Just the fact that you know you are in an experiment can cause change.
Whether the lights were brighter or dimmer, production went up in the Hawthorne electric plant.

17. Experimentation Review
A summary of steps during experimentation.

18. Let’s do an experiment. Hypothesis: The red pill will reduce anxiety.
We operationalize the definition of anxiety to mean those whose doctors claim they suffer from anxiety.
We find 100 people who fit the operationalized definition

19. We randomly assign half the men to the experimental group and half the men to the control group. (Same with women).
I, the researcher, do not know which group will receive the medication and which will receive the placebo. That means this is a double-blind experiment. This will reduce experimenter bias.

20. The experimental group will receive the actual medication
The experimental group will receive the actual medication. (medication - independent variable)
The control group will receive a sugar pill (placebo).
The research team will ask all participants to measure their level of anxiety on a scale from 1 to 10. (Anxiety -dependent variable).
The control group will usually report a decrease in anxiety even though they received no medicine. This is called the placebo effect.

21. Consider the confounding variables
Consider the confounding variables. This is the stuff that will screw up your experiment.
Ex: what if the control group had a mean age much less than the experimental group? What if the 2 groups had a different percentage of women?

22. Our original hypothesis was: the red pill will reduce anxiety by 40%.
Results: The experimental group reported a mean of 10% reduction in anxiety versus a 5% reduction for the control group.
Theory: After several replications, the medicine has no significant effect on anxiety.

23. Reliability and validity?
A finding is reliable if it can be replicated. If subsequent studies show that the red pill reduces anxiety then the findings are reliable, thus supporting the hypothesis.
A study is valid if it measures what it is supposed to measure. If our experiment measured hypertension instead of anxiety, then the test in invalid, even if it is reliable.

24. Descriptive Methods A.Case studies B. surveys
Type 2 Research methods
What is going on in this picture?
A.Case studies
B. surveys
C. naturalistic observation
We cannot say exactly, but we can describe what we see.

25. A. Case Studies A detailed picture of one or a few subjects.
Tells us a great story…but is just descriptive research.
Does not even give us correlation data.
The ideal case study is John and Kate. Really interesting, but what does it tell us about families in general?

26. B. Survey Method: The Bad
Low Response Rate
People Lie or just misinterpret themselves.
Wording Effects
Ex. Q: Should cigarette ads and pornography be allowed on television? (not allowed vs. forbid)
How accurate would a survey be about the frequency of diarrhea? Homosexuality? Infidelity?

27. Survey Random Sampling
If each member of a population has an equal chance of inclusion into a sample, (unbiased).
If the survey sample is biased, its results are not valid.
The fastest way to know about the marble color ratio is to blindly transfer a few into a smaller jar and count them.

28. False Consensus Effect
Survey
False Consensus Effect
A tendency to overestimate the extent to which others share our beliefs and behaviors.

29. C. Naturalistic Observation
Observing and recording the behavior of animals in the wild and recording self-seating patterns in a multiracial school lunch room constitute naturalistic observation.
OBJECTIVE 7| Identify the advantages and disadvantages of naturalistic observation in studying behavior and mental processes.
Courtesy of Gilda Morelli
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30. Longitudinal studies Cross-sectional study
A subject is studied for a long long long time.
Twins separated at birth are surveyed at ages 5, 10, 15, 20, 30 years.
Cross-sectional study
Different groups of people are compared and contrasted.
Ex. Hispanic vs Caucasion on attitudes towards psychotherapy

31. Types of Correlation Negative Correlation Positive Correlation
Type 3 Research methods
Negative Correlation
The variables go in opposite directions.
Positive Correlation
The variables go in the SAME direction.
Studying and grades hopefully has a positive correlation.
Heroin use and grades probably has a negative correlation.

32. (positive or negative)
Correlation
When one trait or behavior accompanies another, we say the two correlate.
Indicates strength
of relationship
(0.00 to 1.00)
Correlation
coefficient
r = +
0.37
OBJECTIVE 8| Describe positive and negative correlations and explain how correlational measures can aid the process of prediction.
Correlation Coefficient is a statistical measure of the relationship between two variables.
Indicates direction
of relationship
(positive or negative)
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33. Scatterplots
Perfect positive
correlation (+1.00)
Scatterplot is a graph comprised of points that are generated by values of two variables. The slope of the points depicts the direction, while the amount of scatter depicts the strength of the relationship.

34. Scatterplots Perfect negative No relationship (0.00)
correlation (-1.00)
No relationship (0.00)

35. Normal Distribution Which is a stronger correlation? -.13 or +.38

36. Data showing height and temperament in people.

37. Scatterplot
The Scatterplot below shows the relationship between height and temperament in people. There is a moderate positive correlation of

38. Correlational Method
Correlation expresses a relationship between two variable.
Does not show causation.
As more ice cream is eaten, more people are murdered.
Does ice cream cause murder, or murder cause people to eat ice cream?

39. Disconfirming evidence
Illusory Correlation
The perception of a relationship where no relationship actually exists. Parents conceive children after adoption.
Confirming evidence
Disconfirming evidence
Do not
adopt
Adopt
Do not conceive
Conceive
OBJECTIVE 10| Describe how people form illusory correlations.
Michael Newman Jr./ Photo Edit
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40. Why we need research due to human tendency:

41. Hindsight Bias Hindsight Bias is the “I-knew-it-all-along” phenomenon.
Monday Morning Quarterbacking!!!
Hindsight Bias is the “I-knew-it-all-along” phenomenon.
After learning the outcome of an event, many people believe they could have predicted that very outcome.
OBJECTIVE 1| Describe hindsight bias and explain how it can make research findings seem like mere common sense.
“Anything seems commonplace, once explained.” Dr. Watson to Sherlock Holmes.
Two phenomena – hindsight bias and judgmental overconfidence – illustrate why we cannot rely solely on intuition and common sense.
After the Chris Brown/Rihanna incident….my wife said she knew Chris Brown was a violent kid!!! Did she really?
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42. Overconfidence Sometimes we think we know more than we actually know.
82% of U.S. drivers consider themselves to be in the top 30% of their group in terms of safety.
Sometimes we think we know more than we actually know.
Anagram
How long do you think it would take to unscramble these anagrams?
WREAT
WATER
ETYRN
ENTRY
OBJECTIVE 2| Describe how overconfidence contaminates our everyday judgments.
People said it would take about 10 seconds, yet on average they took about 3 minutes (Goranson, 1978).
GRABE
BARGE
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43. Order in Random Events
Given random data, we look for order and meaningful patterns.
The outcome of one toss gives no clue to the next outcome
-no patterns
Your chances of being dealt either of these hands is precisely the same: 1 in 2,598,960.
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44. Random Assignment vs. Random Selection

45. Q1. Can laboratory experiments illuminate everyday life?
FAQ
Q1. Can laboratory experiments illuminate everyday life?
Ans: Artificial laboratory conditions are created to study behavior in simplistic terms. The goal is to find underlying principles that govern behavior.
OBJECTIVE 21| Explain the value of simplified laboratory conditions in discovering general principles of behavior.
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46. Q6. Is it ethical to experiment on people?
FAQ
Q6. Is it ethical to experiment on people?
Ans: Yes. Experiments that do not involve any kind of physical or psychological harm beyond normal levels encountered in daily life may be carried out.

47. Animal Research Clear purpose Treated in a humane way
Acquire animals legally
Least amount of suffering possible.

48. Human Research No Coercion- must be voluntary Informed consent
Anonymity
No significant risk
Must debrief

49. Statistical Reasoning
Statistical procedures analyze and interpret data allowing us to see what the unaided eye misses.
Descriptive Statistics: set of methods to describe data we have collected
Ex. Henry averaged 1 new cars sold for the last 3 Sundays
Inferential Statistics: set of methods used to make generalizations, estimates, predictions
Ex. Henry never sells more than 2 cars on Sunday
OBJECTIVE 15| Explain the importance of statistical principles, and give an example of their use in daily life.
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50. Describing Data
A meaningful description of data is important in research.
Misrepresentation may lead to incorrect conclusions.
OBJECTIVE 16| Explain how graphs can misrepresent data.
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51. Measures of Central Tendency
Mode: The most frequently occurring score in a distribution.
Mean: The arithmetic average of scores in a distribution obtained by adding the scores and then dividing by the number of scores that were added together.
Median: The middle score in a rank-ordered distribution.
OBJECTIVE 17| Describe three measures of central tendency and tell which is most affected by extreme scores.
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52. Measures of Central Tendency
A Skewed Distribution

53. Central Tendency Mean, Median and Mode.
Watch out for extreme scores or outliers.
Let’s look at the salaries of the employees at Dunder Mifflen Paper in Scranton:
$25,000-Pam
$25,000- Kevin
$25,000- Angela
$100,000- Andy
$100,000- Dwight
$200,000- Jim
$300,000- Michael
The median salary looks good at $100,000.
The mean salary also looks good at about $110,000.
But the mode salary is only $25,000.
Maybe not the best place to work.
Then again living in Scranton is kind of cheap.

54. Measures of Variation
Range: The difference between the highest and lowest scores in a distribution.
Standard Deviation: A computed measure of how much scores vary around the mean.
OBJECTIVE 18| Explain two measures of variation.
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55. Standard Deviation

56. Standard Deviation
The Standard Deviation (σ) is a measure of how spread out the numbers are.
The formula is easy: it is the square root of the Variance. So now you ask, "What is the Variance?"
Variance
The Variance (which is the square of the standard deviation, ie: σ2) is defined as:
The average of the squared differences from the Mean.
In other words, follow these steps:
1. Work out the Mean (the simple average of the numbers) 2. Now, for each number subtract the Mean and then square the result (the squared difference). 3. Then work out the average of those squared differences.

57. Example Find out the Mean, the Variance, and the Standard Deviation.
You and your friends have just measured the heights of your dogs (in millimeters):
The heights (at the shoulders) are: 600mm, 470mm, 170mm, 430mm and 300mm.
Mean = = 1970 =

58. Deviation just means how far from the normal
Now, we calculate each dog’s difference from the Mean:
To calculate the Variance, take each difference, square it, and then average the result:
Variance: σ2 =   (-224) (-94)2  =  108,520  = 21,704
Standard Deviation: σ = √21,704 = 147
Standard Deviation: σ = √21,704 = 147
Now we can show which heights are within one Standard Deviation (147mm) of the Mean:
So, using the Standard Deviation we have a "standard" way of knowing what is normal, and what is extra large or extra small.

59. Bell Curve -