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CHAPTER 20 Psychological Research and Statistics.

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Presentation on theme: "CHAPTER 20 Psychological Research and Statistics."— Presentation transcript:

1 CHAPTER 20 Psychological Research and Statistics

2 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

3 Gathering Data  How do psychologists collect information about the topic they’ve chosen to study?

4 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

5 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?

6 Gathering Data  What does correlation mean?  The degree of relatedness between two sets of data  Two types - positive correlation & negative correlation

7 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

8  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

9 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

10 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

11 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?

12  Smile break

13 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??


15 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

16 Experiments  Surveys – an interview/questionnaire that gathers data on the attitudes, beliefs, and experiences of large numbers of people

17 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

18 Experiments  Cross-sectional studies – individuals are organized/studied on the basis of age  Example – Milgram Shock ExperimentMilgram Shock Experiment

19 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

20 Statistics  A branch of mathematics that enables researchers to organize and evaluate the data they collect

21  Smile Break

22 Statistics  Descriptive statistics – listing and summarizing data in a practical and efficient way  Examples – graphs, averages

23 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

24 Frequency Distribution/Histogram

25 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

26 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

27 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

28 Central Tendency  0, 3, 4, 4, 5, 5, 6, 7, 8, 8, 8, 9, 9, 10, 10  Mean – 6.4  Median – 7  Mode - 8

29 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

30 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

31 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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