 0.765 is a pretty high, अगर दो आस्ट्रिक लगे मैं, इसका मतलब है, कोरलेशन अपकी सिएक्निफिकंत है, और हमारी उसने P-Value भी कैल्कलिट करती है, 0.004. तो हमारे 0.01 के उपर results सिएक्निफिकंत है, कुके 0.004 is less than 0.01. तो 0.765 is a significant correlation between the two variables. अगर आप देखें तो ये बेसिकली हमें इस्टा मेट्रिक्स में कोरलेशन देता है, क्रिम्स की प्रिवेंचन के साथ कोरलेशन, प्रिवेंचन की क्रिम्स के साथ. तो वो तार अडेंटी कर दाएगनल होता है, तो ये तो you can report only or look at only one value, which is 0.765. तो औंगे क्ता, फम जो शब लेडिए लगडेन् नगजे क्रिम्स की के साथ हे रूँने भाई, मोझके प्रिवंचन देखेंगे घब कोरलेशन कास्थ, ये औंगे तो लगडेए मैं क्रिम्स देगे वाई, तो तो अडेंगे जर तो आप साथदा गो साथ. the Pearson correlation r is 0.77 you can just go round kardia or p smaller than 0.01 so you will be reporting the r value and then the p value indicating a significant positive correlation between number of crimes and the amount spent on prevention the more number of crimes people commit the more time or amount is spent to prevent these crimes so this is the interpretation and reporting and apart from this if you see how significant our correlation is it is usually given as small, medium, large or for correlation coefficient size of the value of the coefficient ranges from minus 1 to plus 1 the value indicates the strength of the relationship and according to the condition of the cone if it is between 0.1 to 0.29 then it is a small correlation coefficient and if it is between 0.3 to 0.49 then it is medium and if it is above 0.5 then it is a high correlation or large correlation coefficient and same is for the negative as i told you earlier that the sign is just telling us the direction strength or magnitude is not decreasing so as per this cone's criteria the correlation coefficient of 0.65 or 0.77 is a pretty large coefficient correlation which is significant so finally reporting the results as per apa once you conducted a study you tried to find out correlation between the two you will be reporting in this way the relationship between number of crimes in amount spent on prevention was investigated using kiosk and product moment correlation coefficient preliminary analysis were performed to ensure no violation of the assumptions because we had to check the assumptions which i have told you 5-6 assumptions before we run correlation we need to ensure that all our assumptions are being put forward in normality independence scale so assumptions there was a strong significant positive correlation between the two variables r is 0.77 n is 12 and p is smaller than 0.01 with more number of crimes associated with the more time spent on prevention so you will be stating the results so first defining that what have we done then stating the results and then finally interpreting it that what does this correlation mean always remember that whenever you have told the correlation coefficient after that it is necessary to tell that what is the meaning of this 0.77 and even if you report that there is a positive correlation and the coefficient is 0.77 still you need to spell out that if one variable is increasing then what does that mean that if there are more crimes then the amount spent v is more so there is a positive correlation between them