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Lecture 3

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University of Toronto Scarborough
Connie Boudens

Purple text – Prof’s Speech PSYB01 – Lecture 3 Slide 2 – Variables - Definition: something that varies, something that can take on different values o Feature of a person, situation, etc., that can take on one value or more. o Main purpose of psychological research is to simplify the complex by explaining variability in behaviour Slide 3 – Variability in Behaviour - Differences in the way people (or another organism) behave in response to the same stimulus - Types (of variability) : systematic (explained) - random (unexplained)  In psychology random in this case means there is not yet a way to explain the thing o Ex: a mouse runs through the classroom  Possible variables: gender, country/city living, like/dislike of animals, colour of mouse, etc.  People will react in different ways - Variables must have 2+ values or levels o Value: (often a number) number representing one of many possible “states” of the variable o Example: some possible values of height are 6‟, or 4‟2” - Score: a specific value for a given person o Example: my score on the variable of height is 5‟7” Slide 5 – Independent vs. Dependent variable - Independent variable: manipulated by researcher – assumed to be cause - Dependent variable: outcome of experiment – assumed to be caused by i.v. o DV is sometimes called the outcome variable o The DV is only ever measured, not manipulated o DV depends on the IV Slide 6 – Whats the IV? What‟s the DV? - There will be a difference between the number of boys and the number of girls pushing and shoving in the playground o IV – gender o DV – pushing and shoving - There will be a difference between the number 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 o IV – quiet/noisy room o DV - # of words - People who suffer with a serious mental disorder are more likely to take more medication than people who do not suffer with a serious mental disorder. o IV – severity of mental disorder o DV – amount of medication - Students who sit further forward in class will achieve a higher grade in the final examination o IV – closeness to front o DV – final grade - **Exam question ^ Slide 7 – Measuring Variables - First-step: determining whether variable is categorical or continuous. - Categorical (taxonic, qualitative, nominal(in name only)): o Values are discrete, qualitatively different categories o Measured on nominal scale o Ex: biological sex, type of dwelling, political party affiliation - Continuous: o Values differ in degree from each other o Measured on ordinal, ratio, or interval scale o Ex: age, working memory capacity, height, weight - Determines how you can analyse data Slide 8 – Scale of Measurement: Ordinal - Ordered or ranked data - Intervals may or may not be equal - Limiting - Ranked data is hard to do anything with statistically - Ex: finishing place in a race 1 2 3 4 ___|______|___|_____|  Time  Slide 9 – Scale of Measurement: Interval - Ordering, but with equal intervals - Ex: temperature o The „zero point‟ is arbitrary (i.e. zero does not mean none), and values can be negative - Generally, we can analyze ratio data the same way as interval data Slide 10 – Scale of Measurement: Ratio - Same as interval, but with a true zero point (i.e. 0 literally means none; absence of whatever is being measured) - Ex: money in your wallet, time left to finish race, # of friends in the class Slide 11 – Scale of Measurement Summary - Nominal – data may only be classified o Ex: jersey # of football players - Ordinal – data is ranked o Ex: rank in class - Interval – meaningful difference between values o Ex: temperature, dress size - Ratio – meaningful 0 point and ratio between values o Ex: distance to class, # of sales calls made Slide 12 – Measuring Variables - Operational definition: procedures for measuring or manipulating variables; how you‟re going to measure variables - Has to be Specific enough to allow for replication o Straightforward for concrete variables, more challenging for abstract ones - Operational definitions restrict the generalizability of the results - The way you choose to measure a variable is going to affect how it is interpreted Slide 14 – Operational Definitions examples - You hypothesize that people with a few close friends are more healthy psychologically than people with many superficial friendships o How do you measure few – can use a continuous scale, ranges (2-4, etc.) o How do you measure close friend o How do you measure psychological health - You hypothesize that infants who are exposed to a greater variety of visual stimuli will be more creative as toddlers Slide 16 – Relationships between Variables - How do variables related to each other? - No relationship o Ex: height and intelligence in adults - Perfect linear relationship o Opposite of no relationship o Rare in psychology – unless we are talking about something at the micro level o Straight line o One variable is a function of the other  Ex: height in inches and height in cm, mon
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