Class Notes (1,100,000)
CA (620,000)
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PSYB01H3 (200)
Anna Nagy (100)
Lecture

Chapter notes


Department
Psychology
Course Code
PSYB01H3
Professor
Anna Nagy

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Chp 12: B01 – Understanding Research Results: Desc and correlation
Statistics helps to develop an understanding of the collected data
Two reasons for using stats:
Describe data
Make inferences – in the basis of sample data about a population
Scales of measurement:
Whenever a variable is studied
oThere is an operational definition of the variable
oThere must be 2 or more levels of the variable
Recal from chapter 5
The levels of a variable can be desribed using one of the
fourls scales of measurement
oNominal
No numerical or qunatative property
The lvls are just diffrn categories or groups
Most indepdent variables are nominal
Gender, eye color, marital status
oOrdinal
Minimal quantative distinction
We can rank the order the variable from
lowest to highest
Rank of the order of these problems
One problem with this time of level is we
don’t know the interval between them
Its like choclate is my most fav candy and
my second favoire it bubble gum – what is
the difference in liking them a lot ? a little ?
oInterval
Detailed qunatative properties
The intervals in between levlers are equal in
size
The difference btw 1and2 is the same as btw
2and3
Interval scales usually have 5+ quantativie
levels – very negative to very positive
Allow for more sophisticated statistical
treatments then ordinal scales
No absoloute zero point
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oRatio
Detailed qunatative properties
Equal intervals + absoloute zero point
Time weight length
The statistical analysis employed for interval and ratio variables is identical
Data can be summarized
oMean
oUtilizing a number
The scale used – dtrms the type of statistics that are appropriate – when the results
are analyzed
The meaning of a particular score on a variable dpnds
oOn the scale used
Analyzing the Results of Research investigations:
Most research focuses on the study of relationships between variables
Depdending on the way tat the variables are studied – there are 3 basic ways of
describing the results
oComparing group percentages
oCorrelating scores of iniduals on 2 variables
oComparing group means
Comparing group percentages:
Do more male or female like travel?
Correlating invidual scores:
You do no have distinct groups of subjects
Inviduals are measured on two variables – each variable has a range of
numberical values
Frequency Distributions:
Indicates the number of individuals that receive each possible score on a
variable
What can you discover by examining frequency distributions
oHow your participants responded
oShape of distribution
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