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PSY201H1 Study Guide - Comprehensive Final Exam Guide - Variance, Unimodality, Supreme Headquarters Allied Powers Europe


Department
Psychology
Course Code
PSY201H1
Professor
Gillian Rowe
Study Guide
Final

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PSY201H1

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PSY201
Chapter 1 Stats, Science & Observations
Statistics: set of mathematical procedures for organizing, summarizing, and interpreting information
Summarize info to convey results e.g. mean
Justify significance of results
Population: all individuals of interest in a study
Sample: set of individuals selected from pop., usually represents the population of interest
Variable: a characteristic or condition that changes or has different values for different individuals
Datum / score / raw score: one measurement or observation
Data / data set: collection of measurements or observations
Parameter: a value, usually numerical, that describes a population; is usually derived from measurements of the individuals
in the population (WHOLE POP!)
Statistic: a value, usually numerical, that describes a sample; is usually derived from measurements of the individuals in the
sample (NOT WHOLE POP.)
Descriptive statistics: statistical procedures used to summarize, organize, and simplify data
(DESCRIBE RESULTS)
Inferential statistics: techniques that allow us to study samples, then make generalizations about the populations
(INTERPRET RESULTS)
Sampling error: discrepancy between a sample statistic & the corresponding population parameter
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RELATIONSHIPS
(1) Correlation Method
Measure more than one variable for each individual and look for trends (e.g. one + as other +)
DOES NOT SHOW CAUSE-AND-EFFECT
OBSERVE AS THEY EXIST NATURALLY (NO MANIPULATION)
(2) Experimental Method
Comparing two or more groups of scores one variable defines groups, see if other varies
MUST HAVE CONTROLLED VARIABLES & MANIPULATION
SHOWS CAUSE-AND-EFFECT
CONTROLLED VARIABLES
a) Participant variables: age, gender, intelligence vary between subjects
1) random assignment
2) matching (60% M 40% F ratio)
3) holding constant (all 10 y/o)
b) Environmental variables: time, location, weather, etc.
Confounding variable: another variable that could explain results
(fail to control variables, affects dependent AND independent variables)
Independent variable: antecedent variable (prior) that is manipulated
Dependent variable: depends on treatment condition (independent variable), is observed/recorded
Control condition: do not receive experimental treatment or receive a neutral, placebo treatment baseline for comparison
w/ experimental condition.
Experimental condition: do receive the experimental treatment.
(3) Non-experimental Methods
Like correlational studies, because only describe relationships not cause-effect
a) Quasi-experimental: having pre-existing groups that does NOT ALLOW random assignment
Boys vs. girls, 8 year-olds vs. 10 year-olds
b) Pre-post: pre-something and post-something, but passage of time not controlled therefore could be the
confounding variable (other variables changing with time also NOT CONTROLLED)
VARIABLES
Hypothetical constructs: intangible concepts we cannot measure, e.g. intelligence, anxiety, hunger, love
Useful for describing behaviour
Operational definition: identify procedure to measure construct, define construct in terms of that measure (e.g. using IQ
tests to measure intelligence)
Discrete variable: nothing between categories, e.g. number of calls
Continuous variable: infinite possibilities between measurements, e.g. height, weight
Must use boundaries on data real limits: halfway between adjacent scores
MEASUREMENT SCALES (to measure the dependent variable!)
Nominal scale: set of categories that have different names; measurements label and categorize observations, but do not make
any quantitative distinctions btw observations (i.e. one category not > another)
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