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U of M PSY 1001 - Chapter 2 psych

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Chapter 2 Study Guide: Research Methods1. Description (accurate measure important)Prediction (based on our description)Control (using our descriptions and ability to predict to create better environments)2. Describing the world as it is. Naturalistic Observation: Jane Goodall with chimpanzees in Gombe Park. The strength of naturalistic observation is its high external ability, the weakness is the low internal validity, or ourability to draw cause and affect relationships from what we find. Another problem is some may act differently if they know they are being observed. Surveys: Polling the nation on how strongly they feel about religion. The strengths of surveys include how easy they are to perform and the subject often has access to subtle information regarding his or her emotional states about which outside observers aren’t aware. Weaknesses include the assumption that people can report on themselves accurately, which is not always true, and it assumes they are honest, which is not always true. These problems come from positive impression management, or the desire to look better, or from malingering, or the desire to look psychologically disturbed. Case Study: MCNally and Lukach’s case of a man who was sexually attracted to large dogs where they studied and treated him during the study. Strengths include an opportunity to study rare or unusual phenomena that are difficult or impossible to recreate in the laboratory. A weakness is that they typically do not let us explain why a phenomenon occurs because it is not a well conducted study. 3. Examining how strongly to variable are associated with each other. A Strength is once we identifya cause and effect relationship we can predict one variable from the other. Its limitation is that many people fall to illusory correlation, suspicions, or wrongly assuming that all correlations have a cause and effect relationship. The correlation coefficient is a number that measures the strength of a correlation, this scale ranges from -1 to 1, with the strength being the absolute value from 0. (farther from zero, strong correlation) A negative correlation means when one variable goes up, the other goes down, while positive means that move in the same direction. An illusory correlation is the perception of a statistical association between two variables where none exists. The problem of the 3rd variable is that an outside variable, C, caused the variables A and B to move together or directly apart. An example of this is how there is a negative relationship between PHD’s and mules in a state. This is probably due to the difference in rural or urban areasinstead of a relationship between the two. 4. Random assignment and manipulation of an independent variable are the two components of an experiment. Also discussed in the notes are Hypothesis, experimental group, control group, Independent and dependent variable. Experiments are considered the gold standard because they allow us to draw cause and effect conclusions. This is because researches can manipulate variables instead of observe them. Limitations of experiments include how artificial environmentsmay not generalize and we may not be able to manipulate some variables. Generalizability it our ability to claim our findings are accurate to all people of the same group in the same situation. 5. Confounds are a source of false conclusions, or an outside variable that may or may not have affected the result, making the findings meaningless. Experimenter expectancy effect is when the experimenter expects one outcome, and unknowingly swings the result in favor of hisexpectation. Does NOT include someone fixing an experiment in their favor. A double blind design is where neither the researchers nor the participants know who’s in the experimental or control group, to avoid confirmation bias. 6. Central tendency is the sense of the central score in our data set or where the group tends to cluster. The measures include mean median and mode. Mean is the average, median is the score exactly in the middle, and mode is the most frequent score. Standard deviation is the measure of dispersion that takes into account how far each data point is from the mean. 7. The normal curve is the expected distribution in a symmetrical curve. For this instance, mean is the most accurate of the central tendency measurements. 8. Descriptive stats describe data, while inferential stats allow us to determine how much we can generalize findings from our sample to the full population. Statistical significance is when the results were 5% or less likely to have occurred by chance, or if it likely to be accurate results. 9. Measurement is the process of quantifying observations on psychological variables for applied or research purposes. Reliability is the consistency of a measure, like a person’s weight which can be repeatedly measured nearly exactly the same. Validity is if it measures what it was supposed to measure. This debate comes from the accuracy versus consistency topic in statistics. 10. Statistics can have many good uses and can be used to support accurate claims, but if not used correctly (or morally) they can intentionally or accidently mislead us through certain displays thatdo not depict the truth. (like .06 being significant in a large sample size, or using mean in something unevenly distributed, to name a few)11. Every study must pass the IRB’s standards for ethics, including informed consent. The only exception to this is when deception is necessary. Then it needs to be a) critical to the study and b)outweighing the cost and c) debriefing the subject after the study. The qualifications are differentfor animal research, where the debate is much more loosely defined. 12. Heuristics: mental shortcuts or rules of thumb-that help us to streamline our thinking and make sense of our world. Generally this helps us sort through all of the information we receive efficiently, but sometimes it leads to false conclusions.Representative heuristic: Judge the likelihood of an event based on a superficial similarity to a prototype. Availability heuristic: estimate the likelihood of an occurrence based on the ease with which it comes to our minds. Ex. More trees on campus than in a city w/out testing. Base Rate: how common something is. This can be used to defend ourselves from heuristics, even if someone seems likely to be a computer major, if there is 99% of something else in a


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