Another nice tool of Excel is on the x-y scatter plot. You can add a curve-fit line of a more complex nature. Instead of just linear regression, you can also use exponential, logarithmic, and polynomial. It can display the resulting function and corresponding r-squared fit. Great when the data is correlated by something more than simple linear relationship.
The best video ever for beginners from a social science background. Highly recommended. Thank you so much for the guy explaining. He has a talent to explain complex things in such an easy way to understand. God bless him.
This is a great appreciation for us and we are really happy that our efforts are in the correct direction. Thank you so much for your valuable comments 🙏
Im very much willing to learn on this correlation and regression since i was not able to really focus on this during my college days. but first may i ask how or is it possible for me to use correlation and regression on my masters study? like example selection of structures to be used for seismic vulenrability? this willl help me alot if youll respond and it will be very much appreciated. 🙏🙏🙏🙏
First, thank you so much for your valuable comments and appreciation! 🙏☺️ Yes, of course! Correlation and Regression analysis can be used everywhere to see the relationship between variables.
Residuals are computed as (Observed - Expected) and you need to do more tests in order to make sure that your model is corect and stable (when use OLS). 2 important tests: 1 check if the residuals follow a normal distribution, 2 check for heteroskedasticity. On the other hand you explained well
I am slow learner in maths. but you made it so simple to understand. at times, practising by hand makes me lose the focus on what to understand because it is too slow and easy for me to get distracted. but ur way of showing in excel is very effective for me.
Thank you Sir, for your clear explanation. I am able to do my Assignment now. Same for me my Lecturer did not explain this very clearly to us in the two weeks of our Module Business Analysis and Planning.
Generally I do not react to videos easily. But the method chosen here was extremely helpful. Thank you very much sir. Can you please do a video of Types of tests eg: T-Test, Z-test, Chi square Annova ?? maybe you already have done that video.. if yes, please help me with it.
Wow, that's great! Thank you so much for your valuable comments and appreciation 🙏☺ For the videos on mentioned topics, yes, I had already made it. Please visit the playlist named "Hypothesis Testing".
The video assumes that Excel will get it right. But but does not address the underlying theory. While this is useful in a work situation, why not show the answer for the correlation coefficient working from first principles.
Seriously , student need teachers like you sir. Thank you so much , in just 10 mins you explained in such lucid way ,all the concepts which my professor was unable to do even in 3-4 hr class.
why the Pvalue is to be considered 0.05 only. I m getting Pvalue of 0.1(and more for all the variables. Please suggest something. Where is my thing wrong? in data acquisition or any other thing?
p-value is the probability to go with the null hypothesis of "no difference." If it is lower, say 0.05 (5%), we can reject the null hypothesis with a 95% confidence level. For more details, please go through the hypothesis testing.
Thank you for your valuable comments and appreciation! 🙏☺️ For just one x, both statements are correct. For multiple x's, regression is the more appropriate answer.
Thank you for your explanation. Very clear for me. I would like to ask a question, sir. What method can I use if I want to find out the test conditions that produce the same result with two different instruments? Thank you. Sincerely.
Congratulations show direction and degree of relation between 0 and 1. Regression shows this and also how one variable changes due to change in another and numerical relation and prediction can be made
_A scientist determined the intensity of solar radiation and temperature of plantains every hour throughout the day. He used correlation to describe the association between the two variables. A friend said he would get more information using regression. What are your views?_ I wish to understand this better
Of course, you will get more information with the regression as you are going to formulate the equation to explain the relationship between them. This will also explain the percentage of variation in temperature of plantains that is explained by solar radiation.
Thanks for such a wonderful lecture! So can we conclude that regression analysis is the followup of the corelation analysis as to see how to variable are related?
Thank you so much for your valuable comments and appreciation 🙏☺ I had already covered part of these topics in multiple regression analysis videos. I can make some more on this.👍
easy to follow and very clear explanation. Just what I needed. Thank you for using simple terms for those of us that need to understand this topic and are not statistics experts :)
In the example of the temperature to ice-cream sales, how would it be calculated if at a certain temperature people just started staying home instead of going out to get ice-cream?
Thank you for your valuable question. Well, it will be reflected in our regression analysis with R-square value. We might be needed to conduct nonlinear Regression Analysis in that case.
Sir. This is an awesome explanation. I have no words to say how simple you have explained. Thanks a lot Sir. I have liked it and subscribed it. It deserves much more than this.
Indeed a helpful lesson. I intend to work on regression between Groundwater level and rainfall. But I need to do lagged regression for 0month, 1month, 2month, 3month for GW. Can you please provide me some help if possible?
Thank you for your valuable comment. Please let me know how can I help you? You had taken frequency to collect the data monthly. I am sure the requirement would be to study month-wise analysis, then it's okay.
@@learnandapply I want to do regression analysis for monthly noise pollution data for residential areas. How can I predict noise increment with r square in these areas. Next problem which iam facing is in scatter plot, my months are not appearing on the x axis
