SOMALI NATIONAL UNIVERSITY Group “B” Presentation Assignment Title PARTIAL CORRELATION Lecturer: Eng: Ibrahim Rashid

GROUP B STUDENTS 1)Abdukadir Farah Jeyte 2)Abdimajid Ali Abdullahi 3)Abdirahman 4)Ali Abdulla 5)Abdishakur 6)Burhan Said Dirshe 7)Musab 8)Fartun 9)Khadra Abdiwali

Objectives History of partial correlation Definition of partial correlation Desired variables / (Variable numbers) Procedures of partial correlation in SPSS

History Of Partial Correlation History of partial correlation was developed by Karl Pearson and G.Undny Yule. When we intended to measure the effect of several variables on one particular variable then this study related to partial or multiple correlation

PARTIAL CORRELATION Definition: When three or more variables are involved in correlation analysis the correlation between the dependent variable and only one particular independent variable is called “partial correlation”.

conti The influence of other independent variables is excluded in a partial correlation analysis. For example: If we have three variables 1)Yield of wheat 2)Amount of rain fall 3)Application of fertilisers

Partial correlation coefficients provide a measure of the relationship between the dependent variable and other variables, with the effect of the rest of the variables. This "quick start" guide shows you how to carry out a partial correlation using SPSS Statistics, as well as interpret and report the results from this test. However, before we introduce you to this procedure,

you need to understand the different assumptions that your data must meet in order for a partial correlation to give you a valid result. We discuss these assumptions next.

Number of Variables In SPSS Statistics, three variables were created so that the data could be entered: VO2max (a marker of aerobic fitness) (i.e., the person's VO2max, measured in ml/min/kg), Weight (i.e., the person's weight, measured in kg) and Age (i.e., the person's age, measured in years). (Three variables) Note: This is a simple example of partial correlation with a single continuous control variable, but you can include multiple control variables in your analysis.

The six steps below show you how to analyze your data using a partial correlation in SPSS Statistics when none of the five assumptions in the previous section, Assumptions, have been violated. At the end of these six steps, we show you how to interpret the results from this test.Assumptions

Note: In this example we show you how to use the Correlate procedure in SPSS Statistics, which is very straightforward, but it is also possible to use the Regression procedure, which has a number of advantages. For the purposes of a simple example like the one used in this "quick start" guide, we will use the Correlate procedure.

PROCEDURES OF PARTIAL CORRELATION Click Analyze > Correlate > Partial... on the menu system, as shown below:

You will be presented with the following Partial Correlations screen:

Transfer the variables weight and VO2max into the Variables: box, and age into the Controlling for: box, by dragging-and-dropping or by clicking the relevant buttons. You will end up with a screen similar to the one below:

Click the button. You will be presented with the following Partial Correlations: Options screen:

Tick the Means and standard deviations & Zero-order correlations checkbox in the – Statistics– area, as shown below: Click the continue button. Click, OK

This Is The End Thank You