One million thank you's! I learned this stuff back in college, but when it recently came up at work (almost a decade later🤦♀️) I really needed a refresher/crash course! 🤷♀️😭 Thank you, one million and one times! 🙏🤗👍
You're a great teacher sir! I learned this material about a year ago but it's always good to refresh your skills if you don't use them everyday. You're a genius, keep them coming :) I really appreciate it.
Thank you for your summary. My company asked me to learn how to be a forecast analyst. I am looking for a way to master this material. Your explanation was very helpful. You are a good teacher. Congratulations on a job well done.
Very informative...I've one question, why didn't you take the MAD= 6.16 in calculating the Tracking signal based on the formula.. and what is the difference between the two?
Thanks for informative videos. Could you tell further that out all error accuracy determination methods you explained which one is most effective? Is it MAD ,MAPE or tracking signal?
Tracking signal is a method to judge if the current forecasting method is good enough, so per se, it is not a method to determine forecast accuracy. Between MAD and MAPE I don;t think it matters what you choose. Since MAPE is in per cent, you can compare accuracy across products. For MAD, it is very easy to calculate and understand.
Thank you, Nice lesson. recently, I'd like to do the Time series analysis-trend about climate such as rainfall, temperature for predicting 5 years, 10 years by using mann kendall test method. Could you please give me some example how to predict rainfall or temperature in future 5 years and 10 years using mann kendall test method? Thank you so much for your kind.
If this is an academic question - we have many research papers that deal with the issue, for example www.sciencedirect.com/science/article/pii/S0169207016000121 And, if this a real life problem, I need more data, for MAPE may not be the right measure for you.
