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CHAPTER 20 Psychological Research and Statistics
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Objectives Describe the process of psychological research Name the different types of psychological research and some of the methodological hazards of doing research Describe descriptive and inferential statistics Name specific research methods used to organize data
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Gathering Data How do psychologists collect information about the topic they’ve chosen to study?
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Gathering Data Validity – verifying that a claim is correct, or disproving it A claim cannot be valid until it has been repeatedly tested and found to be true Example: Fashion magazine advertisements (“thicker” hair, no wrinkles, rapid weight loss) Innocent until proven guilty – have to be found guilty in order for your arrest to be valid
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Gathering Data Sample – relatively small group out of the total population Population – an entire group as a whole Sample must be representative of the population If a sample is not representative, then it is biased How can researchers avoid bias?
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Gathering Data What does correlation mean? The degree of relatedness between two sets of data Two types - positive correlation & negative correlation
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Gathering Data IQ scores and academic success – positive correlation (direct relationship) The higher your IQ, the higher your grades Car speed and time it takes to travel somewhere – negative correlation (inverse relationship) - as car speed increases, time it takes to reach your destination decreases
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Your turn! Hours in the sun and chance of sunburn Positive correlation Amount of exercise and % body fat Negative correlation Mr. Cline’s high school GPA and your high school GPA no correlation
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Experiments Why do researchers choose experimentation over other research methods? Researchers can control the situation. The goal of research is to prove or disprove a... Hypothesis
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Experiments Variables – conditions and behaviors that are subject to variation/change Two types of variables – independent and dependent IV – manipulated variable in order to view its effects DV – dependent upon the IV – affected by it
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Experiments Experimental group – consists of subjects who undergo the experimental treatment – variables are applied to this group Control group – consists of subjects who do not receive experimental treatment Why is this group necessary?
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Smile break
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Experiments Naturalistic observation – viewing the subjects of an experiment in their natural habitat IMPORTANT: Subjects CANNOT know they are being watched! Why is this important??
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ACTIVITY TIME!
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Experiments Case study – a scientific biography of a group or person Most use long-term research to gather tons of data in order to generate new hypotheses Stanford Prison Experiment Stanford Prison Experiment
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Experiments Surveys – an interview/questionnaire that gathers data on the attitudes, beliefs, and experiences of large numbers of people
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Experiments Longitudinal studies – covers a long period of time Psychologists study subjects over regular intervals for a period of years Allows for examination of consistencies and inconsistencies
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Experiments Cross-sectional studies – individuals are organized/studied on the basis of age Example – Milgram Shock ExperimentMilgram Shock Experiment
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Avoiding Errors How can researchers avoid errors while doing research? self-fulfilling prophecy - Researchers finding what they want to find, while overlooking contrary evidence Example experiment – testing a new medicine Single Blind – subjects do not know if they have a placebo or the real thing Double Blind – subjects AND experimenter have no knowledge of who has the real medicine/placebo
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Statistics A branch of mathematics that enables researchers to organize and evaluate the data they collect
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Smile Break
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Statistics Descriptive statistics – listing and summarizing data in a practical and efficient way Examples – graphs, averages
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Statistics Frequency distribution – table that arranges data in a way that allows us to see how often a particular score occurs Histogram – similar to bar graphs – always vertical & the bars always touch
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Frequency Distribution/Histogram
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Central Tendency Central tendency – a number that describes something about the “average” score Used to summarize information into statistics Measures of CT: mean, median mode
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Central Tendency Mean – an “average” score Most commonly used measure of CT To find the mean, you add all scores and divide by the number of scores
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Central Tendency Median – the middle score The midpoint of a set of scores, so it divides the frequency distribution into two halves Mode – the most frequent score
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Central Tendency 0, 3, 4, 4, 5, 5, 6, 7, 8, 8, 8, 9, 9, 10, 10 Mean – 6.4 Median – 7 Mode - 8
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Measures of Variance Distributions show us not only the “average” score, but also how “spread out” these scores are. Variance – provides an index of how spread out the scores of a distribution are
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Measures of Variance Range – subtract the lowest score from the highest score Standard deviation – a measure of distance, describing an “average” distance of every score to the mean The larger the standard deviation, the more spread out the scores are
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Inferential Statistics Used to determine whether or not the data that researchers collect supports their hypotheses, or whether their results are merely due to chance outcomes probability & chance Ex – flipping a coin – each toss is independent of eachother If probability that results are due to chance is less than 5%, researchers can be confident in their findings
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