I am finding out the relationship between culture shock and Exam scores of a group of participants. I have the culture shock level and marks both at the end of 1st semester and 2nd semester. How can I calculate a single value of correlation? Do I just check it at the end of any semester or should I combine the data for both semesters? The participants are the same for 1st semester and 2nd semester.
Indunil Karunarathna
Understand the Data: Ensure a clear understanding of your variables and the nature of the pre-post relationship which you're investigating. Collect Data: Collect data from your participants for both the pre and post-conditions. Check Assumptions: Before conducting Pearson's correlation, ensure that your data meets the assumptions of this test. These assumptions include: Both variables should be normally distributed. There should be a linear relationship between the variables. There is homoscedasticity, meaning that the variances along the range of values are more or less equal. Compute Pearson's Correlation Coefficient: Once you have confirmed the assumptions are met, you can apply Pearson's correlation coefficient using statistical software or programming languages such as Python, R, or SPSS. The formula for Pearson's correlation coefficient (r) is: r=∑(Xi−X)(Yi−Y)/ ∑(Xi−X2)(Yi−Yˉ))...........sorry the equation cannot be typed here. Look into a standard reference, please. Interpret the Correlation Coefficient: The correlation coefficient ranges from -1 to 1. A value close to 1 indicates a strong positive linear relationship. A value close to -1 indicates a strong negative linear relationship. A value close to 0 indicates no linear relationship. Assess Significance: Determine whether the correlation coefficient is statistically significant. You can do this by comparing the correlation coefficient to a critical value from a table of Pearson correlation coefficients at your decided significance level (typically 0.05 or 0.01), or by conducting a hypothesis test using software. Interpret Results: Based on the obtained result of the correlation coefficient and its significance, conclude the relationship between your variables.
To check Pearson's correlation between two variables in the same group of participants, you'll typically follow these steps:
Note, correlation does not imply necessarily causation. Even if you find a significant correlation between variables, it doesn't necessarily mean that changes in one variable cause changes in the other.
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