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Finding Answers Begins by Finding Questions.docx

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Steve Joordens

PSYA01 Sept. 19/24 Scientific process usually begins with a theory… Somebody’s explanation meant to explain what they’ve seen. ‘Good’ theories lead to hypotheses…. Predictions that can be empirically tested in a way that might prove them to incorrect (i.e. falsifiable).  Freud’s theories of human behaviour and religious existence theories (creationism) are often criticized for being un-falsifiable and therefore, impossible to test. o Freud’s idea of the conscious couldn’t be tested:  ID – wants right away without worrying about consequences  Superego – wants to be best person possible  Ego – works to balance out the other two parts Falsifiable is what is wanted by scientists because it means it can be tested. How to find theories Naturalistic Observations Goal of observations: to find patterns in behaviour. Pros: the researcher is placed right into the culture/environment. Cons: mere presence of researcher and the act of observation can change a situation.  Example: an alien is in a class to study them. The class reacts with shock and is uneasy. This is no longer normal behaviour. Jane Goodall wanted to understand chimpanzee culture so she went to live with the chimps in their environment. Variable  Used to refer to anything that can take on multiple values. o Ex. eye colour can have values of green, blue, brown etc.  categorical: people fall into certain categories o Ex. height  This is continuous because it lies on a continuum (A continuous sequence in which adjacent elements are not perceptibly different from each other, although the extremes are quite distinct).  A variable is continuous or categorical, based on how it is measured. PSYA01 Sept. 19/24 Descriptive Statistics If you measure some variable across many people you can sometimes end up with a lot of date to make sense of when it’s presented in raw form.  Example: asking a group of students how old they are and receiving these results: o 21, 20, 23, 21, 23, 22, 20, 21, 22, 22, 21, 25, 19, 22, 21, 23, 26, 24 Frequency distribution (using example) Age Frequency 19 1 20 2 Measure of Central Technology 21 5 22 4 Mean: The point that is the minimum possible distance from all of 23 3 the other points in the sample. 24 1  Extremes of the data (highest and lowest results) can 25 1 26 1 confuse the data.  Example: 22 Median: the point that have the data points lie half above and half below.  Example: 22 Mode: the most frequently occurring data point or observation  Example: 21 Measure of Variability
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