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Lecture 1

PSYC 210 Lecture Notes - Lecture 1: Statistical Inference, Descriptive Statistics, Standard Deviation


Department
Psychology
Course Code
PSYC 210
Professor
Snjezana Huerta
Lecture
1

Page:
of 8
Topic I: Introductory Material
• Syllabus– Introductions
– Course objectives and organization– Creating an environment conducive to learning – Student
deliverables and evaluation– Course schedule
• Describing Data – Terminology
– Format of datasets
• Measurement in Psychology– Stevens’ scales of measurement– Data transformations (& their
implications) – Some issues and considerations
Statistics
The word statistics is often used to refer to the:1. Set of procedures or rules used to summarize
some
characteristic or relation in a sample and 2. Resulting outcomes(The term does not refer to the
data.)
There are two classes of statistics covered in this course:
• Descriptive statistics: Describe and summarize the data
• Inferential statistics: Characteristics of the sample are used to make inferences about the
population’s characteristics
Describing Data: Some Distinctions
• Parametersversusstatistics• Variablesversusconstants• Dichotomousversuspolytomousvariables
• Discreteversuscontinuousdata• Quantitativeversusqualitativedata
Describing Data: Some Distinctions
PARAMETER /
STATISTIC
A numerical quantity that summarizes a characteristic of the population
A numerical quantity that summarizes a characteristic of the sample
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-denoted using Roman letters e.g., the mean level of some variable, X, at the
-denoted using Greek letters
population level (ÎĽX) and for a sample (X )
This is an unique identifier, assigned by the researcher to link related information and maintain
anonymity
Describing Data: Some Distinctions
ID Group
VARIABLES and CONSTANTS
Age(G) (X; in mo.)
Math (M/100)
ScaleUp (C)
Variables
Constant
Describing Data: Some Distinctions Dichotomous versus polytomous variables
– Dichotomous Variables: only 2 response options
e.g.:• pass/fail• yes/no• clinical/notclinical • 0/1
– Polytomous Variables: more than 2 response options
e.g.:
•never/sometimes/always
•blonde/red/brunette/black/grey/white/other
•0/1/2/3/4/5/6/7
Describing Data: Some Distinctions
Discrete Data
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Continuous Data
• Attributes or objects that can be represented with a scale consisting of whole units only
• Attributes or objects that can be represented with a scale that includes fractions or parts of a
whole
(no fractions)
e.g., categories, frequencies or counts
e.g., weight, height, relative frequencies or proportions
Describing Data: Some Distinctions
Qualitative Data
Quantitative Data
• Cases are differentiated in terms of two or more qualities or categories
• Cases are differentiated in terms of the quantities of an attribute they possess
• Measurement in Psychology– Stevens’ scales of measurement– Data transformations (& their
implications) – Some issues and considerations
Measurement in Psychology What is Measurement?
• The systematic assignment of numbers to phenomena of interest (e.g., objects or responses; see
Howell, 2007; Stevens, 1936, 1946)
• The ordering of data using a particular scale; that is, we seek “a scale adequate to the
measurement of the [phenomenon of interest]” (Stevens, 1936, p. 405)
• There are different systems of rules for assigning numbers depending on the kind of
information collected; Stevens (1946)Ń° identified four scales of measurement
Ń°Stevens wrote a number of articles on the issue of measurement; this is but one.
Measurement in Psychology Why Measure?
• For the purposes of representing and, possibly, comparing phenomena –
“torepresentaspectsoftheempiricalworld”(Stevens,1946,p.677)–
“torepresentfactsandconventionsabout[things]”(Stevens,1946,p.680)
• Ideally, to represent phenomena and the relations amongst them using mathematical formulas
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