Unit 2 Research Methods Module 4 The need for Psychological Science Critical Thinking “Smart thinking” Four elements Examines assumptions Discerns hidden values Evaluates evidence Assesses conclusions Unit 2 Research Methods Psychology is Empirical. It is based on research. Before we delve into how to do research, you should be aware of common hurdles that tend to skew our logic. James Randi test psychics on abc https://www.google.com/webhp?sourceid=chrome-instant&ion=1&espv=2&ie=UTF8#q=james+randi+test+psychics+on+abc+for+the+one+million&safe=active&tbm=vid 1. Hindsight Bias Hindsight bias is the tendency to think that past events were more predictable than they actually were. Also known as the “I knew it along”. Did you know I was going to play this? http://www.youtube.com/watch?v=-bayV3wez50 Knowing about hindsight bias is useful in two ways: Firstly, it gives you something to say when your parents accuse you of failing to predict an event. You can accuse him of having hindsight bias.(Well, it's better than saying "Yeah, we know that now!") Imagine that you receive a letter from a publisher that states that the publisher is going to publish your short story. You tell a friend that you knew that they would publish it. 2. Overconfidence We like to think we know more than we do For Example: Some quizzes, people rate their answers as "99% certain" but are wrong 40% of the time. A person who thinks his sense of direction is much better than it actually is. A person who thinks he is much smarter than he actually is. Confirmation Bias: (Barnum effect)A tendency for people to accept information that confirms what they want believe Psych335 - Confirmation Bias - Team 16 http://www.youtube.com/watch?v=fc0tiNGi8jw&feature=related Hawthorne Effect: Experimenter Bias: Just knowing you are participating in a study can change the outcome. Pg. 43 http://www.youtube.com/watch?v=IxZoxN5IjFE http://www.propagandaposters.us/poster11.html 4. Hawthorne Effect http://www.youtube.com/watch?v=W7RHjwmVGhs Hawthorne Effect: Experimenter Bias: Just knowing you are participating in a study can change the outcome. Pg. 43 Just the fact that you know you are in an experiment can cause change. http://www.propagandaposters.us/poster11.html Why do we have Ethical Guidelines The next couple of slides are horrible experiments that explain why it is necessary. During WWII the Nazi’s conducted some very unethical studies. Many of their subjects died during theses experiments. What you need to know is: 1. These people were denied the principles in the Belmont Report including being asked to participate. Milgram Study (1963): The Milgram study involved instructing subjects to administer electric shocks to a study confederate in response to poor performance. The subject believed that he/she was involved in a study about learning and memory with each shock intended to affect the learning process. The confederate pretended to be hurt by the shock - in some cases, to the point of losing consciousness; however, he/she did not really feel any shock. The study objective was to assess obedience to authority. This study resulted in significant psychological stress for some subjects including sweating, trembling, stuttering and serious seizures in three subjects. The question of whether this study was ethical remains open to debate among scholars today. http://www.youtube.com/watch?v=BcvSNg 0HZwk Stanford Experiment A group of men volunteered for a study and were given the roles of prisoners or guards. In a short time the guards took it upon themselves to start trouble with the prisoners and the experiment got out of hand. Lesson in “the Lucifer” Effect. How good guys turn bad. https://www.youtube.com/watch ?v=RKW_MzREPp4 Tuskegee Syphilis Study: In 1932, the Public Health Service enrolled several hundred syphilitic black males to document the effects of the untreated disease over time. Tuskegee was chosen because approximately 40% of the male population of the town was infected with the disease. Treatment was withheld from study subjects when penicillin was accepted as the treatment for syphilis in 1943. This study was stopped in 1973 but not before many subjects became seriously ill, transmitted their disease to others or died. This study exemplifies unfair subject selection practices denial of informed consent and excessive risk in relation to study benefits. Ask me to show you the video located in Unit 2 Videos! I am telling you this because I know I won’t remember where I put it and will spend half an hour looking for it. Thank you, you are very nice people. http://www.youtube.com/watch?v=j6bmZ8cVB4o Can I just start any old research project I want to? No, I need permission from the IRB first. Institutional Review Board. They make sure you are following all ethical guidelines. Why do we have to have this? There have been many unethical studies done. When doing a Research study the first step is to get permission from the IRB: Protection of Participants Privacy Consent Withdrawal, Confidentiality Deception Debriefing Write a brief description of each: 1. Protection from Harm: 2. Debriefing: 3. Privacy: 4. Informed Consent: 5. Deception: 6. Right to Withdrawal: Animal Research: YES: Otherwise important issues could not be investigated. Relativity little animal research involves pain or harm. NO: Animals are entitled to the same rights as humans. Animal studies are often trivial or may not apply to humans. Ethics worksheet Speed theory http://www.youtu be.com/watch?v=i ynzHWwJXaA Theory: http://www.youtube.com/watch?v=2lXh2n0aPyw explanation of some aspect of the natural world that is acquired through the scientific method, and repeatedly confirmed through observation and experimentation …Aims to explain Hypothesis: is a testable prediction that lets us accept, reject or revise a theory. If families do not stress gender differences then there will be fewer sex differences in siblings. Example: (not the one you can use). Music influences concentration in study halls. The null hypothesis states that there is no relationship or difference between two sets of data. When conducting a psychology experiment, you can either not reject the null hypothesis (suggesting that there is no relationship between the variables) or reject the null hypothesis (suggesting that there is a relationship between the variables). For example, let's suppose that you are conducting an experiment on the effect of sleep deprivation on math scores. Your hypothesis is that students who receive less than five hours of sleep the night before a mathematics exam will do worse than students who sleep for more than five hours. After performing your experiment, you find that there is a statistically significant relationship between sleep deprivation and math scores, which means that you can reject the null hypothesis. Identify the: 1. Control Group 2. Independent Variable 3. Dependent Variable 4. What should Smithers' conclusion be? Smithers thinks that a special juice will increase the productivity of workers. He creates two groups of 50 workers each and assigns each group the same task (in this case, they're supposed to staple a set of papers). Group A is given the special juice to drink while they work. Group B is not given the special juice. After an hour, Smithers counts how many stacks of papers each group has made. Group A made 1,587 stacks, Group B made 2,113 stacks. Identify the7. Control Group 8. Independent Variable 9. Dependent Variable 10. What should Homer's conclusion be? Homer notices that his shower is covered in a strange green slime. His friend Barney tells him that coconut juice will get rid of the green slime. Homer decides to check this this out by spraying half of the shower with coconut juice. He sprays the other half of the shower with water. After 3 days of "treatment" there is no change in the appearance of the green slime on either side of the shower. Experimental Group: Receives Treatment Control Group: receives no treatment Beware of Confounding 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. Validity and Reliability Valid: it is accurate. The extent to which a test or experiment measures or predicts what it is supposed to. Reliable: It can be replicated. Repeating the essence of a research study. Get a partner. Get lego’s, sheet of paper, markers, pencils You will have 10 minutes Double Blind vs. Single Blind When conducting research, it is almost always impossible to study the entire population that you are interested in. As a result, researchers use samples as a way to gather data. A sample is a subset of the population being studied. It represents the larger population and is used to draw inferences about that population. six-sigma-material.com http://mips.stanford.edu/courses/stats_data_analsys/lesson_1/234_0_a.html Random Sampling From a population if each member has an equal chance of inclusion into a sample, we call that a random sample (unbiased). If the survey sample is biased, its results are questionable. The fastest way to know about the marble color ratio is to blindly transfer a few into a smaller jar and count them. BAD Finding the average height of men or women by using basketball players for your sample. Give me a few more. Random Sample: equal chance of being picked. Random Assignment: Equal chance of being assigned to a group. Placebo: “sugar pill” that is given and the patient believes to be the real thing. Operational definition: is one makes it clear how the Researcher should go about measuring the process, activity, or thing. EG. Hunger for example might be defined as “hours without eating” When you word statements carefully with an operational definition you make it possible for others to replicate your study. Let’s say your hypothesis is that chocolate causes violent behavior. • What do you mean by chocolate? • What do you mean by violent behavior? Methods of Research There are 3 categories: Descriptive, Correlational and Experimental We like Survey’s because: 1. They are cheap 2. you can get a large amount of information quickly. We don’t like Survey’s because: 1. Accuracy depends on the ability and willingness of the participants. 2. Sampling Bias can skew results 3. Bad questions can corrupt data Survey False Consensus Effect A tendency to overestimate the extent to which others share our beliefs and behaviors. http://www.youtube.com/watch?v=7dJLzXFOC_I Naturalistic Observation Good: Let’s you observe in a participants natural setting. There is Hawthorne effect. bad The is that we can never really show cause and effect. •Observer can alter behavior •Observational Bias •Cannot be generalized •More accurate than reports after the fact •Behavior is more natural http://www.youtube.com/watch?v=fSiWXkOfHBY&feature=related Research project that investigates the degree to which two variables are related to each other. Does NOT say that one variable causes another. There is a positive correlation between ice cream and murder rates. Does that mean that ice cream causes murder? Correlation does NOT mean Causation!! Good: Determines relationship between 2 variables. Predicts future behavior. Bad: Will uncover a relationship but that does not mean it is the cause https://www.youtube.com/watch?v=8B271L3NtAw Correlations also vary in the strength of the association Zero correlation: no relationship between the 2 variables Strong correlation: knowing the value of one variable permits one to accurately estimate the value of the other variable Strong correlation can be positive or negative Correlations can be seen in scatter plots © 2004 John Wiley & Sons, Correlational Research The correlation coefficient a statistical measure that indicates the degree of association between 2 variables Correlations vary in direction: Positive association: increases in the value of variable 1 are associated with increases in the value of variable 2 Negative association: increases in the value of variable 1 are associated with decreases in the value of variable 2 No relation: values of variable 1 are not related to variable 2 values © 2004 John Wiley & Sons, How to Read a Correlation Coefficient Redelmeier and Tversky (1996) assessed 18 arthritis patients over 15 months, while also taking comprehensive meteorological data. Virtually all of the patients were certain that their condition was correlated with the weather. In fact the actual correlation was close to zero. Ice cream sales and the number of shark attacks on swimmers are correlated. • Skirt lengths and stock prices are highly correlated (as stock prices go up, skirt lengths get shorter). • The number of cavities in elementary school children and vocabulary size are strongly correlated. Cross-Sectional Studies: Data is collected from groups of individuals of different ages and compared. Advantages Disadvantages data on many variables increased chances of error data from a large increased cost number of with more subjects subjects http://www.youtube.com/watch?v=6EjJsPylEOY Done in a lab. Good: You have control over your environment, can determine the cause and effect of an experiment. Bad: You don’t see behaviors in their natural surroundings. Case Studies An intense study of a person or group. Diaries, Tests, and interviews. Pros: Rich description of subject, easy to control Cons: Observer bias, difficult to summarize subject's experience Data is taken from a group over a period of time. http://www.google.com/imgres?imgurl=http://www.cfr.nichd.nih.gov/images/children_linedup2.jpg&imgrefurl=http://www.cfr.nichd.nih.gov/longitudinal.html&usg=__w_lHT2-TFLy8l_gLnyOF8W7ctE=&h=364&w=589&sz=68&hl=en&start=0&zoom=1&tbnid=J01pJhEZ4AmeM:&tbnh=99&tbnw=160&prev=/images%3Fq%3Dlongitudinal%2Bstudies%26um%3D1%26hl%3Den%26sa%3DN%26rlz%3D1T4ADRA_enUS376US377%26biw%3D1899%26bih%3D922%26tbs%3Disch:1&um=1&it bs=1&iact=rc&dur=334&ei=OheETPijDIn4swPDutH2Bw&oei=OheETPijDIn4swPDutH2Bw&esq=1&page=1&ndsp=37&ved=1t:429,r:10,s:0&tx=61&ty=59 Advantages Disadvantages data easy to collect data collection method may change over time easy to present in graphs difficult to show more than one variable at a time easy to interpret needs qualitative research to explain fluctuations can forecast short term trends assumes present trends will continue unchanged How can math and psychology be related? Just describes sets of data. You might create a frequency distribution. Frequency polygons or histograms. A branch of math that summarizes and makes meaningful inferences from the data. http://www.blinkx.com/watch-video/amazing-statistics/ERt_t-mY1EwAypRxeXdO_Q Frequency is how often something occurs. Frequency Distributions: list of scores from highest to lowest. What type of graph would you use to show a frequency distribution? Typically, a bar graph. Let’s make one: Scores from voc. Quiz. 30, 54, 27, 46, 38, 42, 55, 51, 55, 42, 38, 42,31, 55 Put the numbers in order, then added up: •how often 1 occurs (2 times), •how often 2 occurs (5 times), •etc, and wrote them down as a Frequency Distribution table What can you see? Mode the most frequently occurring score in a distribution Mean the arithmetic average of a distribution obtained by adding the scores and then dividing by the number of scores Median the middle score in a distribution half the scores are above it and half are below it Which is best (mean, median, or mode)? It would not be a good idea to use the mean to report the central tendency for housing costs in a community because most communities have a few very valuable homes. When you calculate a mean, these few expensive homes will affect the mean much more than each of the moderately priced homes will. As a result, housing will appear to be more expensive than it really is. Another time when we usually prefer the median over the mean (or mode) is when our data is skewed (i.e., the frequency distribution for our data is skewed). as the data becomes skewed the mean loses its ability to provide the best central location for the data because the skewed data is dragging it away from the typical value Measures of Central Tendency http://www.youtube.com/watch?v=VuRyosm3t-s • Mean is generally used, unless extreme values (outliers) exist — then median is often used, since the median is not sensitive to extreme values. Team I has range 6 inches, Team II has range 17 inches. Disadvantages of the Range •Ignores the way in which data are distributed •Only uses two entries from the data set •Sensitive to outliers . http://rchsbowman.wordpress.com/2010/09/01/statistics-notes-%E2%80%94-measures-of-variation/ Skewed Distributions A skewed distribution represents a set of scores or numbers that is not equal on both sides. ttp://www.sophia.org/identifying-positive-skew/identifying-positive-skew-tutorial?topic=measures-of-shape • Outliers skew distributions. • If group has one high score, the curve has a positive skew (contains more low scores) • If a group has a low outlier, the curve has a negative skew (contains more high scores) Statistical Terms 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 Statistical Significance a statistical statement of how likely it is that an obtained result occurred by chance Its symbol is σ The formula is easy: it is the square root of the Variance. So now you ask, "What is the Variance?" Variance The Variance is defined as: The average of the squared differences from the Mean. To calculate the variance follow these steps: Work out the Mean (the simple average of the numbers) Then for each number: subtract the Mean and square the result (the squared difference). Then work out the average of those squared differences. (Why Square?) http://www.youtube.com/watch?v=pFGcMIL2NVo Normal Distribution http://www.youtube.com/watch?v=xgQhefFOXrM&feature=related Z score 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” http://www.youtube.com/watch?v=oHGr0M3TIcA Inferential Statistics p value = likelihood that results are a fluke or coincidental Which should you trust more, results with a low or high p value? How low? If p < 0.05, then the results are “statistically significant”. Statistically significant – not likely due to random chance Infer your data get it infer hahahahaha Probability and Significance: Probability, or p, is expressed as a number between 0 and 1. 0 means an event will not happen, 1 means that an event will definitely happen. The P value will always be found to be between 0 and 1 due to the way in which it is calculated. To calculate the probability that a particular outcome will occur, it has to be divided by the number of possible outcomes. One way to work out the probability of something occurring is to use this formula: Probability = number of particular outcomes number of possible outcomes http://www.youtube.com/watch?v=BE54mDs6St4