PSYC496AV Lecture Notes - Statistical Significance, Anxiety Disorder, Internal Validity

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12 Feb 2013
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Epidemiological research
Epidemiology is the study of the frequency and distribution of a disordered in a
population
Data re gathered about the rates of a disorder and its possible correlates in a large samples
or population
Epediologioical research focuses on determining three features of a disorder:
1) prevalence- the proportion of a population that has the disorder at a given point or
period fo time
2) incidence- the # of new cases of the disorder that occur in some period of time usually
a year
3) risk factors- conditions or variables that if present increase the likelihood of
developing the disorder
knowing this stuff is imp for planning health care facilities, services, etc
depression is twice as common in women than men. Thus gender is a risk factor and this
knowledge led to a theory of depression that suggests its due to a style of coping with
stress that is more common in women than men
The correlational method
correlational method - establishes whether there is a relationship between or among two
or more variables
it is often employed in epidemiological research
in correlatioanl research the variables being studied are measured as they exits in nature
this feature distinguishes the method from experimental research in which variables are
actually manipulated and controlled by the researcher
ex: national study of Canadian preschoolers showed that behaviour problems were higher
among kids from less affluent neighbourhoods
Measuring correlation
1st thing in determining a correlation is to obtain parts of observations of the variables in
question. Ex: height and weight
Then the strength of the relationship between the two sets of observations can be
calculated to determine the correlation coefficient denoted by the symbol r. the statistic
may take any value between –1.00 and +1.00 and it measures both the magnitude and the
direction of a relationship
The higher the absolute value of r, the larger or stronger the relationship between the two
variables.
An r of either +1.00 or –1.00 indicates the highest possible or perfect relationship
whereas an r of 0.00 indicates that the variables are unrelated
If the sign of r is positive the two variables are said to be positively related –as the values
for variable x increase those for variable y also tend to increase. Ex: correlation between
height and weight is +.88 this would indicate a very strong positive relationships as
height increased so does weight
When the sign of r is negative, variables are said to be negatively related as scores on one
variable increase those for the other tend to decrease. Ex: # of hours spent watching t.v is
negatively correlated with grade point average
Scatter diagrams of positive and negative correlations
In perfect relationships all points fall on a straight line
The values tend to scatter increasingly and become dispersed as the correlation becomes
lower
When the correlation reaches 0.00 knowledge of a persons score on one variable tells us
nothing about his or her score on the other
Statistical significance
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