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PSYB01 - Lec 3: near-verbatim (Boudens)

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Connie Boudens

PSYB01 Lecture 3: Basic Issues and Concepts PY Date: Slide 1: o The scientific approach: Observation/insight Hypothesis Testing todays focus Slide 2: o Variables: Definition: something that varies; can take on diff values feature of an object that can have more than 1 value (psych: its going to be person/animal mostly) examples: level of creativity, # of siblings, color food, height, weight purpose of psych research: simplify the complex by exploring key variables that can explain differences in behaviour; which variable is responsible for the way an organism responds in particular situation Slide 3: Variability in behaviour o Differences in the way ppl (or other organisms) respond to the same stimulus Why is it/what are the things that create the differences in the way ppl react? o Types: Systematic (explained) Variable that weve been able to explain Random Unexplained variation o Ex) mouse runs thru the classroom Ppl may react differently; why ppl react in diff ways; help predict beh; why diff kinds of beh exists; why the variation Care about stimulus that has diff effects on ppl; not so much about variable that has same effect on ppl o Variables? Gender? City vs. country person? Animal lover? Color of mouse? Still some variation in responses left between people This is randomfor now. In theory, should be able to find everything that causes differences btn ppl in future, brain imaging methods, research methods related to neurology be able to explain all variation But at this point, there is still random variation (not explained) Slide 5: o Variables must have 2+ values or levels (if not, it doesnt vary, not variable) o Value: one of the many possible states of the variable Ex) some values for height: 64 inches, 52 inches o Score: a specific value on that variable for a given person 1 PSYB01 Lecture 3: Basic Issues and Concepts PY Date: More than just what they get on a particular test; its what they get on a particular variable 3x) my score in the variable height is 57 inches Slide 6: Independent vs. dependent variables o Independent (iv, IV): Variable thats manipulated by researcher If experiment, then manipulated; if not experiment, the IV is the variable that is measured Cause of w/e phenomenon youre looking at; usually behaviour = phenomenon o Dependent: Never manipulated; always measured Outcomes variable Assumed to be caused by IV o The DV depends on the IV; DV is caused by changes in the IV Slide 7: Whats the independent variable and whats the dependent variable? o Ex) There will be a difference btn the # of boys and the # of girls pushing and shoving in the playground. IV: Gender DV: pushing and shoving o Ex) There will be a difference btn the # of words recalled by participants who have learned them in a noisy room and participants who have learned the same words in a quiet room. IV: level of noise in room 2 levels: o Noisy room o Quiet room DV: # of words recalled o Ex) People who suffer w/ a serious mental disorder are more likely to take more meds than ppl who dont suffer from serious mental disorder. IV: Severity of disorder Levels: o Serious o Everyone else DV: Amt of meds taken o Ex) Students who sit further forward in class will achieve higher grade. IV: Where you sit Levels not quantified; depends on study/set-up DV: Grade in the course Hard to know whether causal relationship; usually done as correlational study Slide 8: Measuring Variables o 2 types: Categorical (aka: taxonic, qualitative, nominal) Values discrete = not overlapping Qualitatively diff from each other; the categories Measured on nominal scale 2PSYB01 Lecture 3: Basic Issues and Concepts PY Date: o Nominal means = in name only Ex) biological sex, political party affiliation, dwelling Gender not thought of as categorical; thought to be on continuum Continuous Values differ in degree Ex) height, weight, age, working memory capacity, how much time taken to do something Can be put on dimensional thing Measured on ordinal, ratio, or interval scales o When you go to set up a study, have to be careful of the types of variables that you decide to include b/c it can really limit the study that you do Ex) if youre only measuring 2 categorical variables; look at whether men and women will differ wrt supporting a certain political party These are both categorical variables; theres very little that you can actually do with the numbers; wont tell you as much as continuous variables With continuous variables, can have a lot of different possible values of that particular variable; finer distinctions and more things can be done The key thing that the diff kinds of measurements tell you is how you can analyze the data o You can have a variable like age, which is continuous but can be taken as a categorical variable with 2 possibilities: under age 25 and over age 25
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