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Research Methods Unit 2 1 Hindsight Bias 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. 2 Overconfidence We tend to think we know more than we do. 82% of U.S. drivers consider themselves to be in the top 30% of their group in terms of safety 81% of new business owners felt they had an excellent chance of their businesses succeeding. When asked about the success of their peers, the answer was only 39%. (Now that's overconfidence!!!) 3 The Barnum Effect It is the tendency for people to accept very general or vague characterizations of themselves and take them to be accurate. The Scientific Attitude The scientific attitude is composed of curiosity (passion for exploration), skepticism (doubting and questioning) and humility (ability to accept responsibility when wrong). 5 Scientific Method Psychologists, like all scientists, use the scientific method to construct theories that organize, summarize and simplify observations. 6 Applied V. Basic Research • Applied Research has clear, practical applications. • YOU CAN USE IT!!! • Basic Research explores questions that you may be curious about, but not intended to be immediately used. Studying how kissing changes when you get older is interesting…but that’s about it. Research on therapies for drug addicts has a clear purpose. Scientific Method 1. Observe some aspect of the universe. 2. Invent a theory that is consistent with what you have observed. 3. Use the theory to make predictions. 4. Test those predictions by experiments or further observations. 5. Modify the theory in the light of your results. 6. Go to step 3. 8 Theory A Theory is an explanation that integrates principles and organizes and predicts behavior or events. For example, low self-esteem contributes to depression. 9 Hypothesis A Hypothesis is a testable prediction, often prompted by a theory, to enable us to accept, reject or revise the theory. People with low self-esteem are apt to feel more depressed. • All hypothesis’s must have operational definitions & be replicable. 10 Null Hypothesis • the hypothesis the researcher tries to disprove. • The researcher never proves or accepts the null hypothesis, but can only reject it or not reject it Example: Hypothesis: Roses exhibit greater rate of growth when planted in soil rather than compost. Null Hypothesis: Roses do not exhibit greater rate of growth when planted in soil rather than compost. • 2nd example….You might see it written like this: H1: Gender has an effect on spatial ability H0: Gender does not have an effect on spatial ability 11 Operational Definitions • precise statements of the procedures (operations) used to define the variables • Example – Anxiety is a concept that most of us are all too familiar with. It is an unpleasant feeling that occurs in certain situations. It can disrupt our functioning if it is excessive, but it also motivates behavior. So how do you measure it? How do you operationally define anxiety? 12 Operational definitions continued • Since this is a concept that we have first-hand knowledge of, we might start the process of operationally defining anxiety by asking ourselves what it is like. What do we feel? How do we react? How do others react? What features in other people would suggest to us that they are anxious? – Self reported answers – Physiological arousal (heart beating fast, sweating, shaking, trembling, nervous stomach, stomach ache, accelerated breathing, rise in temperature, decrease in temperature, etc…) Lets try coming up with a few A psychologist wants to know if his new form of psychotherapy will make people less depressed. College athletes are not as smart as regular students. The teacher wants to find a way to help make Billy act more friendly toward the other children 13 Replicate (Replication) • repeating the essence of a research study, usually with different participants in different situations, to see whether the basic finding extends to other participants and circumstances • Doing it again to see if you get the same results 14 What is going on in this picture? We cannot say exactly, but we can describe what we see. Thus we have….. Descriptive Research • Any research that observes and records. • Does not talk about relationships, it just describes the situation 15 Types of Descriptive Research • Case Study Method • Survey Method • Naturalistic Observation Method 16 Case Study A technique in which one person is studied in depth to reveal underlying behavioral principles. https://abdullaman.wordpress.com/2011/05/01/five -landmark-psychology-case-studies-you-shouldknow-about/ 17 Clinical Case Study is a form of case study in which the therapist investigates the problems associated with a client. http://behavioralhealth.typepad.com You cannot apply what you learn from a case study to the entire population. 18 Survey A technique for ascertaining the self-reported attitudes, opinions or behaviors of people usually done by questioning a representative, random sample of people. http://www.lynnefeatherstone.org 19 The Survey Method • Used in both descriptional and correlational research. • Use Interview, mail, phone, internet etc… • The Good- cheap, anonymous, diverse population, and easy to get random sampling (a sampling that represents your population you want to study). 20 Survey Method: The Bad • Low Response Rate • People Lie or just misinterpret themselves. • Wording Effects How accurate would a survey be about the frequency of diarrhea? 21 Wording Effect or Framing Wording can change the results of a survey. Q1: Should nude ads be allowed on TV? Or Q2: Should nude ads be forbidden on TV? The second question adds a value judgement and can sway the way people think 22 Random Sampling If each member of a population has an equal chance of inclusion into a sample, it is called a random 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. 23 Why do we sample? • One reason is the avoid the False Consensus Effect: The tendency to overestimate the extent to which others share our beliefs and behaviors. 24 Population • All the possible people or cases within a specific group – Example: • I want to know what students of at SMHS think about the food in the cafeteria – My population is every single student at SMHS » There is NO way I’m going to be able to get to survey EVERY student, so I would take a RANDOM SAMPLE » I’d pass out surveys during all the lunches to each student that walked into the cafeteria on a given day. » Those students that returned the survey are now part of my sample 25 Naturalistic Observation • Observing and recording behavior in natural environment. • No control- just an observer. What are the benefits and detriments of Naturalistic Observation? What did Jane Goodall do? 26 Correlational Research • Detects relationships between variables. • Does NOT say that one variable causes another. (Correlation DOES NOT EQUAL CAUSATION) Did you know that there is a relationship between ice cream sales and murder rates. Does that mean that people who buy ice cream are murders? Or that eating ice cream causes you to murder someone? 27 Correlation When one trait or behavior accompanies another, we say the two correlate. Indicates strength of relationship (0.00 to 1.00) Correlation coefficient Correlation Coefficient is a statistical measure of the relationship between two variables. r = + 0.37 Indicates direction of relationship (positive or negative) 28 Scatterplots Line of best fit or regression line is the smooth line that reflects the general pattern in a graph. You can draw a line through each dot 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. 29 Scatterplots Negative correlation As one variable goes up the other goes down You can look at the correlational coefficient to see if there is a negative sign (-) after the r = Positive correlation As one variable goes up the other goes up or as one goes down the other goes down You can look at the correlational coefficient to see if there is a positive 30 sign (+) after the r = Example Scatterplot The scatterplot below shows the relationship between height and temperament in people. r= +0.63 Illusory Correlation The perception of a relationship where no relationship actually exists. Parents conceive children after adoption. Adopt Confirming evidence Disconfirming evidence Do not adopt Disconfirming evidence Confirming evidence Michael Newman Jr./ Photo Edit Conceive Do not conceive 32 The Experiment • Only research method capable of showing cause and effect Experimental Research • Explores cause and effect relationships. Eating too many bananas causes Constipation 34 The st 1 few steps of an experiment • You have your question & your hypothesis • Pick your population • You have to randomly sample individuals from your population • Your sample must be a representative sample – a sample that accurately reflects the characteristics of the population as a whole 35 Stratified sampling • a process or selecting individuals from a population in such a way that the subgroups in the population are represented in the sample, the population is divided into subpopulations and random samples are taken of each stratum. – At SMHS we have a very diverse population so I would need to make sure each subgroup is represented in my sample. Now you have your participants for your experiment. What do you do next? 36 Random Assignment • Assigning participants to one of the condition groups in such a way that all participants have equal chance of being chosen. 37 Groups (must be randomly assigned) Experimental group • Group that has the experiment done on them • Receives the Independent variable (IV) – The variable the experimenter manipulates Control Group • Group that DOES NOT have the experiment done on them • Does NOT receive the independent variable 38 Variables • Independent Variable (I.V.): what is manipulated by experimenter – The effect of the independent variable is the focus of the study. • Dependent Variable (D.V.): What is MEASURED or influenced by the independent variable • Confounding/Extraneous variables – Other variables that can effect the outcome of the experiment or study that were not controlled for or can not be controlled Example When examining the effects of breast feeding upon intelligence Breast feeding is the independent variable Intelligence is the dependent variable Are there other variables that effect intelligence? Those would be confounding or extraneous variables 40 Control Measures • Single-Blind: subjects are unaware of their assignment group • Double-Blind: subject and experimenter unaware of placement – Best to use to avoid experimenter and participant bias More Control Measures Placebo: inert substance that is in place of IV in Control Group. Placebo effect: results caused by expectations alone; any effect on behavior caused by the administration of an inert substance or condition 42 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. Other Research Method Ex Post Facto (after the fact) • Research in which we choose subjects based on a preexisting condition like race or gender • Not a true independent variable • No cause and effect • Often used due to ethical concerns • Describes differences between groups of participants that differ naturally Flaws in Research happen • • • • • Sampling Bias Overgeneralization Placebo effect Hawthorne & Barnum effect Demand Characteristics – a subtle cue that makes participants aware of what the experimenter expects to find or how participants are expected to behave. Can change the outcome of an experiment because participants will often alter their behavior to conform to the experimenters expectations • Experimenter Bias Comparison Below is a comparison of different research methods. 46 Evaluating Research You need to know the STRENGTHS AND WEAKNESSES of each of the following: Experiment Correlation Surveys Naturalistic Observation Case Studies Descriptive Statistics • Just describes sets of data • You might create a – frequency distribution – frequency polygons – Histogram Measures of Central Tendency • Mean – average score • Mode – most reoccurring score • Median – middle score • The mean salary is about $110,000 so I can say the mean salary is $110,000 (I pay my employees very well). But is that really the case? • The median salary looks good at $100,000. • But the mode salary is only $25,000. Maybe my data shows that my company is not the best place to work. Let’s look at the salaries of the employees at one company $25,000- cashier $25,000- stock room $25,000- assistant manager $100,000- manager $100,000- manager $200,000- regional manager $300,000- owner To calculate the mean: Add up all the salaries ($775,000) and divide by the number of people (7). To calculate the median, I put all the scores in order (See above). The Normal Curve 50 51 Skewed Distributions • Negatively Skewed – When a distribution includes extreme scores that are unusually high • Positively Skewed – When a distribution includes extreme scores that are low 52 Skewed Scores • Positively skewed • Negatively skewed 53 Measures of Variation • Range: – distance between the highest and lowest scores • Variance: – the degree to which a set of values varies from the mean of the set of values • Standard Deviation: – average amount by which the scores in a distribution deviate around the mean. • Z-scores: – tells you how far the raw score is away from the mean in terms of standard deviation units Standard Deviation: the variance of scores around the mean. • The higher the variance or SD, the more spread out the distribution is. • Do scientists want a big or small SD? Shaq and Kobe may both score 30 points per game (same mean). But their SDs are very different. Standard Deviation 56 Scores • A unit that measures the distance of one score from the mean. • A positive z score means a number above the mean. • A negative z score means a number below the mean. Inferential Statistics Inferential Statistics • Interpret data and draw conclusions • Used to test validity of hypothesis (t-test) • Determine whether or not findings can be applied to the larger population from which the sample was selected – Making sure the results are not due to sampling error and chance Sampling error • the extent to which a sample differs from the population 58 When is a Difference Significant? When sample averages are reliable and the difference between them is relatively large, we say the difference has statistical significance or is statistically significant. For psychologists this difference is measured through alpha level (ᾁ) set at .05% or 1% 5% (p<.05) or 1% (p<.01) level of significance 59 Statistical Significance If the results are statistically significant • The difference is NOT due to Chance • Meaning the manipulation of the IV created a change in the DV • If the results were NOT statistically significant • then the results WERE due to chance and the manipulation of the IV did not cause a change in the DV 60 Ethical Guidelines for Research • APA • IRB- Institutional Review Board • Rules for both humans and animals. APA Ethical Guidelines for Human Research All research goes before an institution review board (IRB) for approval Research involving humans must meet the following standards: 1. Coercion-participants cannot be forced in any way to participate in the study 2. Informed Consent-participants must know that they are involved in research and give their consent or permission 3. Anonymity/Confidentiality -the identities and actions of participants must not be revealed in anyway by the researcher 4. Risk -participants cannot be placed at significant mental or physical risk. DO NO HARM 5. Debriefing -participants must be told of the purpose of the study and provided with ways to contact the researchers about the results after the study is complete Deception-if the participants are deceived in any way about the nature of the study the participants must be debriefed after the study is over 62 Ethics for Animal Research • Clear scientific purpose • Treated & cared for in a humane way • Acquire animals legally • Least amount of suffering possible…Do No Harm • A trained psychologist must supervise all research with animals