Presentation on theme: "1 Thinking Critically with Psychological Science Chapter 1."— Presentation transcript:
1 Thinking Critically with Psychological Science Chapter 1
2 Scientific Method Psychologists, like all scientists, use the scientific method to construct theories that organize, summarize and simplify observations. 1.Making observations 2.Defining a problem 3.Proposing a hypothesis 4.Gathering evidence/ testing hypothesis 5.Publishing results 6.Theory building
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 A Theory is an explanation that integrates principles and organizes and predicts behavior or events. For example: low self-esteem contributes to depression. Theory
5 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. Research Observations
1.Making observations computer game designers have varying levels of stress 2.Defining a problem In what ways are high stress and low stress game designers different? High control vs. Low control? 3.Proposing a hypothesis Game designers who have more control over difficult tasks will report less stress 4.Gathering evidence/ testing hypothesis (Randomly assign subjects into two groups: A.Forced pace (low control) = high stress B.Self pace (high control) = low stress 5.Publishing results –write and publish article 6.Theory building use the results to create theory that explains having control over a task reduces stress 6
7 Comparison Below is a comparison of different research methods.
8 Experimentation 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
To Perform an Experiments 1.Directly vary a condition you think might affect behavior 2.Create 2 or more groups of subjects –Should be alike in all ways except the condition varying 3.Record whether varying condition have a effect on behavior 9
1. Experimental subjects/objects A. Experimental group B. Control group 2.Variable- any condition that can change or affect the outcome of experiment A.Independent variable B.Dependent variable C.Extraneous Variable 10
11 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. Independent Variable If there is a drug in an experiment, the drug is almost always the independent variable.
Dependent Variable The dependent variable would be the effect of the drug. Whatever is being measured in the experiment. It is dependent on the independent variable. For example, in our study on the effect of breast feeding upon intelligence, intelligence is the dependent variable.
Beware of Confounding/Extraneous Variables If I wanted to prove that smoking causes heart issues, what are some confounding 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. Lifestyle and family history may also effect the heart.
14 In evaluating drug therapies, patients and/or experimenters assistants should remain unaware of which patients had the real treatment and which patients had the placebo treatment. Evaluating Therapies Single-blind & Double-blind Procedure Placebo Effect Experimenter Effect
15 Assigning participants to experimental (Breast- fed) and control (formula-fed) conditions by random assignment minimizes pre-existing differences between the two groups. Evaluating Therapies Random Assignment
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.
Lets 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
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.
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.
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?
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.
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 C. naturalistic observation Type 2 Research methods We cannot say exactly, but we can describe what we see. What is going on in this picture?
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?
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 Survey A tendency to overestimate the extent to which others share our beliefs and behaviors. False Consensus Effect
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. Courtesy of Gilda Morelli
Longitudinal studies 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
Types of Correlation Positive Correlation The variables go in the SAME direction. Negative Correlation The variables go in opposite directions. Studying and grades hopefully has a positive correlation. Heroin use and grades probably has a negative correlation. Type 3 Research methods
32 Correlation When one trait or behavior accompanies another, we say the two correlate. Correlation coefficient Indicates direction of relationship (positive or negative) Indicates strength of relationship (0.00 to 1.00) r = Correlation Coefficient is a statistical measure of the relationship between two variables.
33 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. Scatterplots
34 No relationship (0.00) Perfect negative correlation (-1.00) Scatterplots
Normal Distribution Which is a stronger correlation? -.13 or or or +.04
36 Data 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
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 Illusory Correlation The perception of a relationship where no relationship actually exists. Parents conceive children after adoption. Confirming evidence Disconfirming evidence Do not adopt Disconfirming evidence Confirming evidence Adopt Do not conceive Conceive Michael Newman Jr./ Photo Edit
Why we need research due to human tendency: 40
41 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. Hindsight Bias After the Chris Brown/Rihanna incident….my wife said she knew Chris Brown was a violent kid!!! Did she really? Monday Morning Quarterbacking!!!
42 Overconfidence Sometimes we think we know more than we actually know. Anagram BARGEGRABE ENTRYETYRN WATERWREAT How long do you think it would take to unscramble these anagrams? People said it would take about 10 seconds, yet on average they took about 3 minutes (Goranson, 1978). 82% of U.S. drivers consider themselves to be in the top 30% of their group in terms of safety.
43 Given random data, we look for order and meaningful patterns. Order in Random Events Your chances of being dealt either of these hands is precisely the same: 1 in 2,598,960. The outcome of one toss gives no clue to the next outcome -no patterns
Random Assignment vs. Random Selection 44
45 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.
46 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.
Animal Research Clear purpose Treated in a humane way Acquire animals legally Least amount of suffering possible.
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
50 Describing Data A meaningful description of data is important in research. Misrepresentation may lead to incorrect conclusions.
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.
52 Measures of Central Tendency A Skewed Distribution
Central Tendency Mean, Median and Mode. Watch out for extreme scores or outliers. $25,000-Pam $25,000- Kevin $25,000- Angela $100,000- Andy $100,000- Dwight $200,000- Jim $300,000- Michael Lets look at the salaries of the employees at Dunder Mifflen Paper in Scranton: 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.
55 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: σ 2 ) 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.Mean 56
Example Find out the Mean, the Variance, and the Standard Deviation. Mean = = 1970 = 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.
Deviation just means how far from the normal Now, we calculate each dogs difference from the Mean: To calculate the Variance, take each difference, square it, and then average the result: Variance: σ 2 = (-224) (-94) 2 = 108,520 = 21,704 5 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. 58