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Chapter 1

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University of Guelph

Psychology

PSYC 1010

c

Fall

Description

Chapter 1- An Intro to Stats & Research Design
Two Branches of Statistics:
1. Descriptive Statistics
- Summarize numerical information about a sample
- Organize, summarize, and communicate a group of numerical observations
2. Inferential Statistics
- Draw conclusions about the broader population based on numerical
information from a sample
- Use sample data to make general estimates about the larger population
Variables: observations of physical, attitudinal, and behavioural characteristics
- Quantified with discrete or continuous observation
Discrete Observations
- Only specific values, no other values can exist between these numbers (ex.
Whole numbers)
- Nominal Variables- Categorical
Used for observations that have categories or names as their values
(ex. Male- #1, Female- #2)
- Ordinal Variables- Ranked
Observations that have rankings as their values (ex. 1 place, 2 nd
place)
Continuous Observations
- Can take on a full range of values, an infinite number of potential values
exists
- Interval Variables- Scale
Used for observations that have numbers as their values (ex. Time- the
interval from 1s to the next is always the same)
The distance (or interval) between pairs of consecutive numbers is
assumed to be equal
- Ratio Variables- Scale
Variables that meet the criteria for interval variables but also have
meaningful zero points (sometimes discrete) (has a true zero point)
- Scale Variable
Meets the criteria for an interval variable or a ratio variable
Three Types of Variables
Levels: the discrete values or conditions that variables can take on
- Variables vary (i.e. a variable can be anything from time to gender)
Independent Variable
- Has at least two levels that we either manipulate or observe to determine its
effects on the dependent variable
Dependent Variable
- The outcome variable that we hypothesize to be related to, or caused by,
changes in the independent variable (depends on the independent variable)
The independent variable predicts the dependent variable Confounding Variable
- Any variable that systematically varies with the independent variable so that
we cannot logically determine which variable is at work (ex. During a
hurricane it is unclear as to whether a home was destroyed by

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