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PSYC 210 Chapter Notes -Count Data, Dependent And Independent Variables

Course Code
PSYC 210
Cathy Mc Farland

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PSYC 210: Introduction to Data Analysis in
CHAPTER 1: Introduction
Statistics – refers to a set of procedures and rules (p.2)
-For reducing large masses of data to manageable proportions and for allowing us to draw
conclusions from those data
-The outcome of the application of those rules and procedures to samples of data; numercal values
summarizing sample data
Descriptive Statistics – purpose is merely to describe a set of data (p.5)
-E.g. average length in time, amount of change, variability of change, etc
Inferential Statistics – hasty generalizations (p.6)
-Generalizing from single (or too limited) observations
-Inference – conclusion based on logical reasoning
-Tool used to estimate parameters of two or more populations, more for the purpose of finding if
those parameters are different than for the purpose of determining the actual numerical values of
the parameters
Population – complete set of events in which you are interested in (p.6)
Parameters – numerical values summarizing population data (p.7)
-e.g. population averages
Sample – set of actual observations; subset of a population (p.7)
Random Sample – a sample in which each member of the population has an equal chance of inclusion
Design Tree – a device for selecting among the available statistical procedures (p.9)
-graphical representations of decisions involved in the choice of statistical procedures
Measurement Data – also called quantitative data (p.9)
-data obtained by measuring objects or events
Categorical Data – also known as frequency data or count data (p.10)
-data representing counts or number of observations in each category
-e.g. 238 voted for a new curriculum, and 118 voted against it
CHAPTER 2: Basic Concepts
Measurement – the assignments of numbers to objects
Scales of Measurement (p.18)
1. Nominal – used only to distinguish among objects (i.e. gender, ethnicity, hair color)
2. Ordinal – used to place objects in order; not necessarily evenly spaced (i.e. never, seldom, often,
3. Interval – scale on which equal intervals between objects represent equal differences; differences
are meaningful (i.e. temperature, pain sensitivity)
4. Ratio – a scale with a true zero point; ratios are meaningful (i.e. time, weight)
oAbsence of the thing being measured
Variables – properties of objects or events that can take on different values (p.22)
1. Discrete variables – variables that take on a small set of possible variables
oi.e. gender, marital status, number of tv’s in one home
2. Continuous variables – variables that take on any value
3. Independent variables – variables controlled by the experimenter
4. Dependent variables – the variables being measured; the data or score