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

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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