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Correlation
• Correlation tells us the relationship between two variables. The
value of ‘r’ (regression) lies between -1 to 1. Here, 1 being the
perfect positive correlation and -1 being the perfect negative
correlation.
• In SPSS, there are three methods of correlation coefficient,
1. Pearson
2. Kendall’s tau-b
3. Spearman
• For our working in SPSS, we are going to test the correlation
between height and weight between male and female.
Step- 1: First, we will add Variables in Variable view ;
ID, Gender, Height & Weight.
Step- 2: Add data in Data View as follows:
• Step- 3: Go to Analyze  Correlate  Bivariate.
• Step- 4: Add the testing variables under the column
‘Variables’.
• Step- 5: Select Pearson and Click ‘OK’.
Output Analysis:
• In this data, the height correlate with weight as both of their r value
came out to be .574. But the sig value of both height and weight is .083,
which is higher than .05, which means that this data is non significant.

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Correlation PPT.pptx

  • 1. Correlation • Correlation tells us the relationship between two variables. The value of ‘r’ (regression) lies between -1 to 1. Here, 1 being the perfect positive correlation and -1 being the perfect negative correlation. • In SPSS, there are three methods of correlation coefficient, 1. Pearson 2. Kendall’s tau-b 3. Spearman • For our working in SPSS, we are going to test the correlation between height and weight between male and female.
  • 2. Step- 1: First, we will add Variables in Variable view ; ID, Gender, Height & Weight. Step- 2: Add data in Data View as follows:
  • 3. • Step- 3: Go to Analyze  Correlate  Bivariate. • Step- 4: Add the testing variables under the column ‘Variables’. • Step- 5: Select Pearson and Click ‘OK’.
  • 4. Output Analysis: • In this data, the height correlate with weight as both of their r value came out to be .574. But the sig value of both height and weight is .083, which is higher than .05, which means that this data is non significant.