Understanding Correlational Research in Psychology

undefined
 
 
Correlational research is designed to 
determine
the degree of relationship 
between 2 or more
variables.
Also referred as “Descriptive Research” or
“Associational Research”.
 
        
Often  naturally occurring variables are:
 
 
 
Intelligence and GPA
Intelligence and GPA
           Aggression and watching TV Shows
           Aggression and watching TV Shows
 
 
 
 Alcohol consumption and driving ability
 Alcohol consumption and driving ability
 
Relationships among two or more variables are
studied without any attempt to influence them.
 
There is no manipulation of variables in
Correlational Research.
With correlational research, we can only show
the magnitude or degree of relationship or
association between variables,
NOT the CAUSE OF RELATIONSHIP.
 
  
Correlational studies 
can suggest that there is a
relationship
 between 
two variables
, they
cannot
 prove that 
one variable 
causes 
a change
in 
another variable
. In other words, correlation
does not 
equal causation
.
   
For example
, a correlational study might suggest
that there is a 
relationship
 between 
academic
success and self-esteem
,
 but it cannot show if
academic success increases or decreases self-
esteem
. Other variables might play a role,
including social relationships, cognitive abilities,
personality, socio-economic status, and a myriad
of other factors.
 
Correlational studies describe the variable relationship
via a 
correlation coefficient.
 
A correlation coefficient identifies
 
Existence
Degree
  [ -1.00 to 0 to +1.00]
 
Direction
 
Sign (+ or -) gives direction of relation
 
The correlation coefficient, denoted by 
r.
 
 
Positive Correlation
 
means that high scores in one variable (X)
are associated with high scores in another variable (Y) and vise versa.
 
A correlation coefficient close to +1.00 indicates a strong positive
correlation.
E.g. 
High attendance ratio can predict high grades.
 
Negative Correlation 
means that high scores in one variable (X)
are associated with low scores in another variable (Y) and vise versa.
 
 A correlation coefficient close to -1.00 indicates a strong negative
correlation.
E.g
. As the amount of addiction toward TV shows increases, the GPA
decreases.
 
No Correlation 
means that change of score in one variable (X) do
not effect scores of another variable (Y).
 
 correlation coefficient of 0 indicates no correlation.
 
 
o
Explaining Important Human Behaviors.
Explaining Important Human Behaviors.
o
Prediction of a Possible
Prediction of a Possible
 
 
Outcome.
Outcome.
 
 
e.g.
e.g.
 High school grades can be used to predict college grades.
 High school grades can be used to predict college grades.
 
Predictor Variable 
Predictor Variable 
is that which is employed to
make a prediction.
         e.g.  High school grades.
 
Criterion Variable 
Criterion Variable 
is the variable about which
the   prediction is made.
e.g.  College grades.
 
 
Observational/Naturalistic research
Type of correlational (i.e., non experimental) research
in which a researcher observes ongoing behavior
e.g. class attendance and grades
 
Survey research
Here researcher selects a sample of respondents from a
population and administers a standardized
questionnaire to them.
e.g. living together and divorce rates
 Archival research
From data already available through
e.g. violence and economics
 
Gives the experimenter the opportunity to
view the variable of interest in a natural
setting.
 
Can offer ideas for further research.
 
May be the only option if lab
experimentation is not possible.
 
Can be time consuming and expensive.
 
Does not allow for scientific control of
variables.
 
Experimenters cannot control extraneous
variables.
 
Subjects may be aware of the observer and
may act differently as a result.
 
It’s fast, cheap, and easy. Researchers can
collect large amount of data in a relatively
short amount of time.
 
More flexible than some other methods.
 
Can be affected by an unrepresentative
sample or poor survey questions.
 
Participants can affect the outcome. Some
participants try to please the researcher, lie
to make themselves look better, or have
mistaken memories.
 
The experimenter cannot introduce changes
in participant behavior.
 
Enormous amounts of data provide a better
view of trends, relationships, and outcomes.
 
Often less expensive than other study
methods. Researchers can often access data
through free archives or records databases.
 
The researchers have not control over how
data was collected.
 
Important date may be missing from the
records.
 
Previous research may be unreliable.
 
Using particular instrument many times,
there is possibility of instrument decay.
 
Care must be taken to ensure observers
don’t become tired, bored or inattentive
 
Unconscious bias on the part of data
gatherers when both instruments are
scored by same person.
 
For example high score in first test may
lead to examiner expectation of high score
in second test.
 
Solution is to have different
administrators for each test.
 
 Threat is there if different persons
   administer both instruments.
 
 For example gender or age may effect
  specific responses, particularly in
  attitudinal instruments.
 
 Can be avoided by having each
   instrument administered by different
   individual.
Basic steps in
Basic steps in
  
  
Correlational Research
Correlational Research
 
The description of problem in hand, which
need to be analyzed.
The problem have to be selected, defined
and delimited.
 
Is variable X related to Y?
How well does variable X predict
variable Y?
 
 What relationships exist among a number
   of variables and what predictions can be
   made based in them?
 
Use random sampling techniques.
Sample size is at least 50 (Gay, 2003).
Samples larger than 50 are much more likely
to provide meaningful results. (Fraenkel &
Wallen, 2005).
It is important to select valid, reliable
measures of variables. If the data is
inadequate it will result in inaccurate
correlational coefficient (Gay,2003).
 
 Data sometimes can be collected from
records of one sort or another(grade
transcripts, for example), most correlational
studies involve the administration of some
type of instrument (tests, questionnaires, and
so on) and sometimes observation.
 
 Instruments to be used has to be 
valid,
reliable and should yield quantitative data.
 
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The result is expressed as a correlation
coefficient.
 
Basic design used in correlational research is straight
forward.
   
 
 
     
     
Observations
Observations
  
 
Respondents
Respondents
 
 
 
 
O
O
1
1
  
  
     
     
O
O
2
2
 
A
  
    ________
 
        ________
 
B
  
    ________
 
        ________
 
C
  
    ________         ________
 
D
 
              ________
 
        ________
 
E
 
              ________
 
        ________
Collect the data 
Collect the data 
 
for each of the variables to
be studied with the use of the instruments
the researcher has prepared/ selected.
 
 Correlation of two variables results in correlation
coefficient.
 
 Correlation coefficient is a decimal number between
0 and -1 and between 0 and +1.
 
 Typically the 
Pearson’s Product Moment
Pearson’s Product Moment
Correlation
Correlation
 
Coefficient or the Pearson’s r
Coefficient or the Pearson’s r
Correlation Coefficient 
Correlation Coefficient 
is used for correlation
analyses.
 
Pearson correlation
This technique is best for linear
relationships.
example is height and weight of growing
children. They are related follow a straight
line.
 
 
 
 
 
 
 
 
 
            Weight
 
-1.00
 
+1.00
 
strong negative
 
strong positive
 
0.00
 
no relationship
Correlation Coefficient
Correlation Coefficient
  
  
                        Relationship
                        Relationship
 
.00 - .20
    
Negligible
 
.20 - .40
    
Low
 
.40 - .60
    
Moderate
 
.60 - .80  
    
Substantial
 
.80 – 1.00
    
High to Very High
 
The scale for describing the 
magnitude of correlation
magnitude of correlation
has to be specified.
 
(Guiford & Fruchter, 1981)
 
 Predictor and criterion don’t usually have a perfect
  correlation.
 
 So, an attempt to use X to predict Y is likely to result
  in a certain degree of error.
 
 Y predicted vs. ‘true/actual’ Y (difference in this is
   known as error score).
 
 The standard deviation of the error scores across all
  individuals is known as SE.
 
 Note: the smaller the SE, the more accurate the
            prediction!
 
y
 
x
 
y
 
x
 
y
 
x
 
y
 
x
 
 Findings for each problem posed in the study are
summarized statistically and conclusions are
summarized statistically and conclusions are
drawn
drawn
.
 
 Recommendations are formulated
 Recommendations are formulated
 b
y the
researcher based on the significant findings noted.
 
Cherry, K. (n.d.) 
Correlational studies: Psychology 
 
research with
correlational studies. 
Retrieved from
 
http://psychology.about.com/od/research
 
methods/a/correlational.html.
 
Fraenkel, R., & Wallen, E.(2005). 
How to Design and 
 
Evaluate
Research in Education
 (6
th
 ed.). San 
 
Fransisco: Corwin.
 
 Gay, L.R.(2003). 
Educational research
 (5
th
 ed.). 
 
Florida:
 
Florida International University.
 
Muller, A. (2002). 
Education, income inequality, and mortality: A
 
multiple regressions. Retrieved 10th july, 2001, from
 
http://www.bmj.com/content/324/7328/23
.
 
The survey system. Retrieved from
 
http://www.surveysystem.com/correlation.htm
 
 
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Correlational research in psychology focuses on determining the degree of relationship between variables without manipulation. It helps show the magnitude of association but not causation. Correlation coefficient indicates the existence, degree, and direction of the relationship between variables. Positive correlation implies high scores in one variable associated with high scores in another, while negative correlation suggests high scores in one variable linked with low scores in another. The purpose of correlational research includes explaining important human behaviors and predicting possible outcomes based on predictor and criterion variables.


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  1. CORRELATIONAL RESEARCH

  2. CONCEPT OF CORRELATIONAL RESEARCH Correlational research is designed to determine the degree of relationship between 2 or more variables. Also referred as Descriptive Research or Associational Research . Often naturally occurring variables are: Intelligence and GPA Aggression and watching TV Shows Alcohol consumption and driving ability

  3. NATURE OF CORRELATIONAL RESEARCH Relationships among two or more variables are studied without any attempt to influence them. There is no manipulation of variables in Correlational Research. With correlational research, we can only show the magnitude or degree of relationship or association between variables, NOT the CAUSE OF RELATIONSHIP.

  4. CONT: Correlational studies can suggest that there is a relationship between two variables, they cannot prove that one variable causes a change in another variable. In other words, correlation does not equal causation. For example, a correlational study might suggest that there is a relationship between academic success and self-esteem, but it cannot show if academic success increases or decreases self- esteem. Other variables might play a role, including social relationships, cognitive abilities, personality, socio-economic status, and a myriad of other factors.

  5. CORRELATION COEFFICIENT Correlational studies describe the variable relationship via a correlation coefficient. A correlation coefficient identifies Existence Degree [ -1.00 to 0 to +1.00] Direction Sign (+ or -) gives direction of relation The correlation coefficient, denoted by r.

  6. CORRELATION COEFFICIENT Positive Correlationmeans that high scores in one variable (X) are associated with high scores in another variable (Y) and vise versa. A correlation coefficient close to +1.00 indicates a strong positive correlation. E.g. High attendance ratio can predict high grades. Negative Correlation means that high scores in one variable (X) are associated with low scores in another variable (Y) and vise versa. A correlation coefficient close to -1.00 indicates a strong negative correlation. E.g. As the amount of addiction toward TV shows increases, the GPA decreases. No Correlation means that change of score in one variable (X) do not effect scores of another variable (Y). correlation coefficient of 0 indicates no correlation.

  7. PURPOSES OF CORRELATIONAL RESEARCH Explaining Important Human Behaviors. Prediction of a PossibleOutcome. o o e.g. High school grades can be used to predict college grades. Predictor Variable is that which is employed to make a prediction. e.g. High school grades. Criterion Variable is the variable about which the prediction is made. e.g. College grades.

  8. TYPES OF CORRELATIONAL RESEARCH Observational/Naturalistic research Type of correlational (i.e., non experimental) research in which a researcher observes ongoing behavior e.g. class attendance and grades Survey research Here researcher selects a sample of respondents from a population and administers a standardized questionnaire to them. e.g. living together and divorce rates Archival research From data already available through e.g. violence and economics

  9. ADVANTAGES OF NATURALISTIC OBSERVATION Gives the experimenter the opportunity to view the variable of interest in a natural setting. Can offer ideas for further research. May be the only option if lab experimentation is not possible.

  10. DISADVANTAGES OF NATURALISTIC OBSERVATION Can be time consuming and expensive. Does not allow for scientific control of variables. Experimenters cannot control extraneous variables. Subjects may be aware of the observer and may act differently as a result.

  11. ADVANTAGES OF THE SURVEY METHOD It s fast, cheap, and easy. Researchers can collect large amount of data in a relatively short amount of time. More flexible than some other methods.

  12. DISADVANTAGES OF THE SURVEY METHOD Can be affected by an unrepresentative sample or poor survey questions. Participants can affect the outcome. Some participants try to please the researcher, lie to make themselves look better, or have mistaken memories.

  13. ADVANTAGES OF ARCHIVAL RESEARCH The experimenter cannot introduce changes in participant behavior. Enormous amounts of data provide a better view of trends, relationships, and outcomes. Often less expensive than other study methods. Researchers can often access data through free archives or records databases.

  14. DISADVANTAGES OF ARCHIVAL RESEARCH The researchers have not control over how data was collected. Important date may be missing from the records. Previous research may be unreliable.

  15. THREATS TO INTERNAL VALIDITY IN CORRELATIONAL RESEARCH

  16. CONT: INSTRUMENT DECAY Using particular instrument many times, there is possibility of instrument decay. Care must be taken to ensure observers don t become tired, bored or inattentive

  17. CONT: DATA COLLECTOR BIAS Unconscious bias on the part of data gatherers when both instruments are scored by same person. For example high score in first test may lead to examiner expectation of high score in second test. Solution is to have different administrators for each test.

  18. CONT: DATA COLLECTOR CHARACTERISTICS Threat is there if different persons administer both instruments. For example gender or age may effect specific responses, particularly in attitudinal instruments. Can be avoided by having each instrument administered by different individual.

  19. CONT: TESTING Responding to first instrument may influence subject responses to second instrument. Solution is to administer instruments at different times and contexts. MORTALITY It is not a problem of internal validity. Loss of subject may create threat to external validity.

  20. Basic steps in Correlational Research

  21. PROBLEM SELECTION The description of problem in hand, which need to be analyzed. The problem have to be selected, defined and delimited. Is variable X related to Y? How well does variable X predict variable Y? What relationships exist among a number of variables and what predictions can be made based in them?

  22. SAMPLE SELECTION Use random sampling techniques. Sample size is at least 50 (Gay, 2003). Samples larger than 50 are much more likely to provide meaningful results. (Fraenkel & Wallen, 2005). It is important to select valid, reliable measures of variables. If the data is inadequate it will result in inaccurate correlational coefficient (Gay,2003).

  23. INSTRUMENTATION & VALIDATION Data sometimes can be collected from records of one sort or another(grade transcripts, for example), most correlational studies involve the administration of some type of instrument (tests, questionnaires, and so on) and sometimes observation. Instruments to be used has to be valid, reliable and should yield quantitative data.

  24. DESIGN AND PROCEDURE Two or more scores are obtained for each member of the sample, one score for each variable of interest, and the paired scores are then correlated. The result is expressed as a correlation coefficient.

  25. DESIGN AND PROCEDURES Basic design used in correlational research is straight forward. Observations Respondents A ________ ________ O1 O2 B ________ ________ C ________ ________ D ________ ________ E ________ ________

  26. DATA COLLECTION Collect the data for each of the variables to be studied with the use of the instruments the researcher has prepared/ selected.

  27. DATA ANALYSIS TECHNIQUES Correlation of two variables results in correlation coefficient. Correlation coefficient is a decimal number between 0 and -1 and between 0 and +1. Typically the Pearson s Product Moment CorrelationCoefficient or the Pearson s r Correlation Coefficient is used for correlation analyses.

  28. CONTINUED Pearson correlation This technique is best for linear relationships. example is height and weight of growing children. They are related follow a straight line. 6 5 4 3 Height 2 1 0 Weight 0 2 4 6

  29. CORRELATION COEFFICIENT -1.00 0.00 +1.00 strong positive strong negative no relationship

  30. PLANNING THE ANALYSIS OF DATA The scale for describing the magnitude of correlation has to be specified. Correlation Coefficient Relationship .00 - .20 Negligible .20 - .40 Low .40 - .60 Moderate .60 - .80 Substantial .80 1.00 High to Very High (Guiford & Fruchter, 1981)

  31. STANDARD ERROR OF ESTIMATE (SE) Predictor and criterion don t usually have a perfect correlation. So, an attempt to use X to predict Y is likely to result in a certain degree of error. Y predicted vs. true/actual Y (difference in this is known as error score). The standard deviation of the error scores across all individuals is known as SE. Note: the smaller the SE, the more accurate the prediction!

  32. A POSITIVE CORRELATION y x

  33. A NEGATIVE CORRELATION y x

  34. NO CORRELATION y x

  35. NO CORRELATION y x

  36. REPORTING THE RESULTS AND CONCLUSIONS OF THE STUDY Findings for each problem posed in the study are summarized statistically and conclusions are drawn. Recommendations are formulated by the researcher based on the significant findings noted.

  37. REFERENCES Cherry, K. (n.d.) Correlational studies: Psychology correlational studies. Retrieved from http://psychology.about.com/od/research methods/a/correlational.html. research with Fraenkel, R., & Wallen, E.(2005). How to Design and Evaluate Research in Education (6th ed.). San Fransisco: Corwin. Gay, L.R.(2003). Educational research (5th ed.). Florida International University. Florida: Muller, A. (2002). Education, income inequality, and mortality: A multiple regressions. Retrieved 10th july, 2001, from http://www.bmj.com/content/324/7328/23. The survey system. Retrieved from http://www.surveysystem.com/correlation.htm

  38. THANKYOU

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