Class Notes (1,100,000)

CA (630,000)

UTSC (30,000)

Psychology (8,000)

PSYA01H3 (1,000)

Steve Joordens (800)

Lecture 2

# PSYA01H3 Lecture Notes - Lecture 2: Standard Deviation, Naturalistic Observation, Central Tendency

by OC1216667

Department

PsychologyCourse Code

PSYA01H3Professor

Steve JoordensLecture

2This

**preview**shows half of the first page. to view the full**3 pages of the document.**Chapter # 2: Reading and Evaluating Scientific Research

Lecture #5

• Scientific process begins with a theory and then turns into a hypothesis: you believe to be

true

• Best theory is the ones that you can find out if it is wrong

• Freud’s theories are bad theories: cannot test anything

• Falsifiable: shown to be wrong

• Pros and cons of naturalistic observation:

➢ Pros: find out things about the study

➢ Cons: presence can change the behaviour of the study

• Variable: is simply anything that can take multiple values (ex. Hair colour, height, etc)

➢ Categorical: the values it can take

➢ Continuous: the values don’t have distinct categories

• Matters have the scientist codes the experiment

• Statistics:

1. Descriptive: one way is to take a set of data and describe it to others clearly

2. inferential: used to answer a question

• Mean: the point is the minimum possible distance from all the other points in the sample

➢ Extreme score can have a powerful effect on the mean

➢ Mean is not accurate in this situation

• Median: the point that have the data points lie above, and half lie down

➢ Used for central tendency

➢ Not sensitive to outliers

• Mode: the most frequently occurring data point or observation

Lecture # 6

• M.A.D: the mean absolute deviation of each data point from the mean of the numbers

• Variance: the average squared deviation of each data point from the mean

➢ Squaring makes the data seem really big

• Standard deviation: take the square root of the squared deviation

• Correlational studies: through observation one think they see links and relations between

different variables

➢ Positive correlation: as one variable gets higher, the other too

➢ Negative correlation: as one variable gets higher, the other gets lower

➢ Zero correlation: no relationship between two variables

• Correlation doesn’t imply causation. Dig deeper with experiments

Lecture # 7

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