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Dr. Engr. Sami ur Rahman Data Analysis Correlational Research.

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Presentation on theme: "Dr. Engr. Sami ur Rahman Data Analysis Correlational Research."— Presentation transcript:

1 Dr. Engr. Sami ur Rahman Data Analysis Correlational Research

2 Correlational Research  Correlational Research is also known as Associational Research.  Relationships among two or more variables are studied without any attempt to influence them.  Investigates the possibility of relationships between two variables.  There is no manipulation of variables in Correlational Research. University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 2

3 Purpose of Correlational Research  Correlational studies are carried out to explain important human behavior or to predict likely outcomes (identify relationships among variables).  If a relationship of sufficient magnitude exists between two variables, it becomes possible to predict a score on either variable if a score on the other variable is known (Prediction Studies).  The variable that is used to make the prediction is called the predictor variable (independent). University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 3

4 Positive Linear Correlation x x y yy x (a) Positive (b) Strong positive (c) Perfect positive

5 Negative Linear Correlation x x y yy x (d) Negative (e) Strong negative (f) Perfect negative

6 No Linear Correlation x x y y (g) No Correlation (h) Nonlinear Correlation

7 Measures strength of the linear relationship between paired x- and y-quantitative values in a sample Sometimes referred to as the Pearson product moment correlation coefficient Linear Correlation Coefficient r

8 where: r = Sample correlation coefficient n = Sample size x = Value of the independent variable y = Value of the dependent variable

9 What Do Correlational Coefficients Tell Us?  The meaning of a given correlation coefficient depends on how it is applied.  Correlation coefficients below.35 show only a slight relationship between variables.  Correlations between.40 and.60 may have theoretical and/or practical value depending on the context.  Only when a correlation of.65 or higher is obtained, can one reasonably assume an accurate prediction.  Correlations over.85 indicate a very strong relationship between the variables correlated. University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 9

10 Thanks for your attention


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