Class Notes
(808,662)

Canada
(493,335)

University of Saskatchewan
(2,891)

Physiology
(96)

PHSI 208
(96)

Neil Hibbert
(30)

Lecture 14

# lecture 14

Unlock Document

University of Saskatchewan

Physiology

PHSI 208

Neil Hibbert

Fall

Description

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
1 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 The magnitude of a correlation coefficient tells us the strength of a relationship between
two variables
Statistical significance refers to the likelihood that the results of an investigation are due
to chance
A statistical significance correlation is one that is not likely to have occurred by chance
A correlation is considered statistically significant if the likelihood or probability that it is
a chance finding is 5 or less in 100. this level of significance is called the .05 level,
commonly written as p =0.5 (p stands for probability)
In general as the size of the correlation coefficient increases the result is more and more
likely to be statistically significant
Whether a correlation attains statistical significance depends on the # of observations
made.
The greater the # of observations the smaller r (the correlation) needs to be to reach
statistical significance
Applications to psychopathology
Whenever we compare ppl given one diagnosis with those given another or with ppl
without a psychological diagnosis the study is correlational
When the correlational method is used in research on psychopathology one of the
variables is typically diagnosis
To calculate a correlation between this variable and another one diagnosis is quantifies so
that having an anxiety disorder is designated by a score of 1 and not having one is score
of 2
The diagnosis variable can then be correlated with another variable such as the amount of
stress that has been recently experiences
Variables such as having anxiety disorder or not are called classificatory variables
other ex are age, sex, social class and body build. These variables are naturally occurring
patterns and are not manipulated
most research on the causes of psychopathology is corrleational
problems of causality
correlatioanl method has a drawback: it does not allow determination of cause-effect
relationships
a sizeable correlation between 2 variable tells us only that they are related or tend to co
vary with each other but we do not really know which is cause and which is effect or if
either variable is actually the cause of the

More
Less
Related notes for PHSI 208