Mam if in a sample population everyone has done the same testing and have to correlate between each by using pearson or any other but my doubt is how can we decide 2 tailed or one - tailed test please explain me in an easy way
The values that you’ve talked about regarding the strength of the relationship between the variables 0.7 to 1 strong and so on, are these values constant? I mean do they apply in every correlation analysis?
1. Strength (strong, moderate and weak) 2. Nature (positive or negative) 3. Significance (significant and insignificant) To see the strength, we have to see the values of pearson correlation. If the values lie in pearson correlation between 0.7 to 1(0.7 to 1) then its shows that the relation is strong if the values lies 0.3 to 0.7 (0.3 to 0.7) then its shows that relation is moderate and if the relation lies less than 3( 0.05 then the relationship between the variable is said to be insignificant and if the P- value < 0.05 then the relationship between the variable is significant. need the sources of the above your statement pls
before run the correlation, the data should fullfill the assumption of the analysis. How could you run gender as a variable for correlation analysis? Gender is nominal data which not full fill the assumption for correlation analysis.
The values that you’ve talked about regarding the strength of the relationship between the variables 0.7 to 1 strong and so on, are these values constant? I mean do they apply in every correlation analysis?
From what I have studied, both variables should be continuous as an assumption for Pearson correlation as it is a parametric test. However, when we have a categorical variable as in this case (gender), we use spearman correlation to get valid and logical results.
Maam is there any way of transferring data quickly to spss by excel bcz we are short of time and getting error on spss though changed data into numeric.
Thank you for the simplicity explanation, by the way I only have one question, what's mean by age is negatively and positively moderate related to salary? What is the difference between positive and negative related?
Positive correlation means one variable is increasing and other is also increasing with the same magnitude. In negative relationship, one is increasing and the other variable is decreasing with the same magnitude.
In regression analysis, R represents the correlation coefficient between variables and R square tells the variance in dependent variable with respect to the independent variable (to put it simply, R square explains that how much independent variable explains independent variable). Pearson correlation parametric, whereas, spearman is non-parametric.
Thanks for such a wonderful way of explaining the interpretation but what is the reference of mentioning the weak strong and moderate relationship and sig value limit
It is important to know how the variables are related to each other. Positive correlation implies that by increase in one of the variable , the other variable will also increase . Similarly negative correlation implies that if one variable incrrases the other will decrease( inverse ). Weak correiation will imply that the variables are loosely related. Significance level is important as it shows the error in data. More that 5% error is not allowed meaning the data is not a good fit
I can't find correlation between my two variables when ran the results they say that can not be computed as at least one of the two variables is constant. Now what to do ?? How to calculate correlation of one of the two variables is constant??
@@QRSchool the variables are basically about two diseases. Presence and absence of disease in patients. There are totally 70 patients. One disease A is present in all 70 patients and second disease B is present in 52 patients ig. I've to calculate the correlation of these two diseases with each other. The result says that correlation can not be calculated as disease A is constant it's all present in all patients . So i wanna know how to calculate correlation in such scenario where one variable is all constant. ??
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If you have any query related please comment below
Please answer my query
What app was used?
Doesn't Pearson work for metric continuous variables only? In this example you used General (nominal) please clarify. Thank you.
Mam if in a sample population everyone has done the same testing and have to correlate between each by using pearson or any other but my doubt is how can we decide 2 tailed or one - tailed test please explain me in an easy way
The values that you’ve talked about regarding the strength of the relationship between the variables 0.7 to 1 strong and so on, are these values constant? I mean do they apply in every correlation analysis?
1. Strength (strong, moderate and weak)
2. Nature (positive or negative)
3. Significance (significant and insignificant)
To see the strength, we have to see the values of pearson correlation. If the values lie in pearson correlation between 0.7 to 1(0.7 to 1) then its shows that the relation is strong if the values lies 0.3 to 0.7 (0.3 to 0.7) then its shows that relation is moderate and if the relation lies less than 3( 0.05 then the relationship between the variable is said to be insignificant and if the P- value < 0.05 then the relationship between the variable is significant. need the sources of the above your statement pls
This is wonderful easy and understandable, thank you so much for simplifying correlation
I think when we have a nominal variable like (Gender) we must use spearman NOT pearson correlation
when the variable is based on some ranking then spearman rank correlation can be used
You're indeed a great and wonderful teacher..... I love you for your teaching simplicity and easy to understand. Thank you so much ❤
You're very welcome!
Thankyouu so muchh ❤
Very well explained 😊
thank you!!! very well explained :D
Thank you ma'am, your teaching style is appreciable
Thank you so much. Your explanation was really good. Very easy to understand
Thank you for the step by step tutorial
before run the correlation, the data should fullfill the assumption of the analysis. How could you run gender as a variable for correlation analysis? Gender is nominal data which not full fill the assumption for correlation analysis.
wow this tutorial is straight forward and very helpful, thank you for your effort.
thank madam for this.
realy very useful aGod bless you maam always !
Mam you won my heart really great your speaking 100%%% your all the ways are. Perfect stay blessed
Mam you won my heart really great your speaking 100%%% your all the ways are. Perfect stay blessed
The values that you’ve talked about regarding the strength of the relationship between the variables 0.7 to 1 strong and so on, are these values constant? I mean do they apply in every correlation analysis?
thnx
This was clear.I didn't understand one point. What is the negative correlation between salary and gender. I didn't understand what is negative.
From what I have studied, both variables should be continuous as an assumption for Pearson correlation as it is a parametric test. However, when we have a categorical variable as in this case (gender), we use spearman correlation to get valid and logical results.
Maam is there any way of transferring data quickly to spss by excel bcz we are short of time and getting error on spss though changed data into numeric.
Yes, you can directly important excel sheet on SPSS. Please see this video: th-cam.com/video/lLbSwKWC-2g/w-d-xo.html
Great job
Thank you for the simplicity explanation, by the way I only have one question, what's mean by age is negatively and positively moderate related to salary? What is the difference between positive and negative related?
Positive correlation means one variable is increasing and other is also increasing with the same magnitude. In negative relationship, one is increasing and the other variable is decreasing with the same magnitude.
Thank you for the very nice lesson. I really appreciate
Hi. Please next time you upload video with captions.
Suggestion noted.
Aesa interpretation mat do atleast
Here in spss, correlation is R or R2 (R square)?. Correlation analysis is a parametric or non parametric technique?
In regression analysis, R represents the correlation coefficient between variables and R square tells the variance in dependent variable with respect to the independent variable (to put it simply, R square explains that how much independent variable explains independent variable).
Pearson correlation parametric, whereas, spearman is non-parametric.
I salute you 🙌 mam
I salute you 🙌 mam
So explanatory and helpful. Thank you 😊
Thanks for the nice lecture. Can you share the SPSS file for practice?
Hello. Primary data can not be shared as this is taken from my research work and it's confidential.
OMG THIS HELPS ME A LOT 😭
I salute you 🙌 mam
beautiful explanantion
please explain Mann-Whitney U-test and Wilcoxon test
Sure I'll make the video
Thanks a lot
Thanks for such a wonderful way of explaining the interpretation but what is the reference of mentioning the weak strong and moderate relationship and sig value limit
It is important to know how the variables are related to each other. Positive correlation implies that by increase in one of the variable , the other variable will also increase . Similarly negative correlation implies that if one variable incrrases the other will decrease( inverse ). Weak correiation will imply that the variables are loosely related. Significance level is important as it shows the error in data. More that 5% error is not allowed meaning the data is not a good fit
Thnx
Mam
At what situations we can use Pearson' correlational test
When you have interval or ratio variable, go for pearson correlation.
easy and understandable
I can't find correlation between my two variables when ran the results they say that can not be computed as at least one of the two variables is constant. Now what to do ?? How to calculate correlation of one of the two variables is constant??
Can you explain a bit about your variables? as it will be easier for me explain the solution.
@@QRSchool the variables are basically about two diseases. Presence and absence of disease in patients. There are totally 70 patients. One disease A is present in all 70 patients and second disease B is present in 52 patients ig. I've to calculate the correlation of these two diseases with each other. The result says that correlation can not be calculated as disease A is constant it's all present in all patients . So i wanna know how to calculate correlation in such scenario where one variable is all constant. ??
@@QRSchool please reply and guide me as soon as possible ✨