 दीस्छौन्त अपका दिसक्छन अं रोंवाग और वो दूग ष्टिजनरिया प्रोचैस चाह। किस तट्टाएप की सीज तो और उसकी ग्राफ्टीकाल आनालिसिस किस टाएप कहोगा कब हमें idea होईगेगा उसके graph देखे, whether the series is stationary or not, then we have specified like formulas जिसे हमें idea होईगेगा, that अगर rho की value equal to 1 है, it means there is unit root, there is like the series is non-stationary. इसी तरा we have another term which is deterministic trend. अगर कोन सेसेरीज होगी जो प्तियोग रन्धंवाक होगी कोन सेसेरीज होगी जिस में deterministic trend होगा, and along with that you can see that there is random walk also there is drift. उसके सास प्ताथ आप उसको देखाखते है, there is random walk also you can see that there is drift. आप नेकस वी हैगेगा like yt is equal to beta 1 plus beta 2t plus beta 3 yt minus 1 plus error term, या आप उसको दिस्टर्बैस ताम भी कैसकते हैं य। have the idea of beta 1 क्या शुओ करते हैं बीटा 2 का येडय है, य। have the beta 3 का येडय है य। have the idea of error term और, उसpecifically, when there is deterministic trend, then बीटा 1 य। is not equal to 0 बीटा 2 य। is not equal to 0 अद बीटा 3 य। is equal to 0 अद बीटा 3 य। is equal to 0 य। means there is no random walk अप की रहाँ नेक्सट याख साथ अज्टार आस्ती्त नहीं हो रहीं तो जस वोगत बीटा 3 य। is equal to 0 वाई ती माँन्स वान की तम जो है येप मोडल से एकसक्लूट होगेगी और अप के पास शिंपल माडल भान जगा yt is equal to β1 plus β2t plus aratum it means that your series is only depending on the time with the passage of time it is changing with the passage of time it is changing we can say that your series is changing series with the passage of time it is changing this is non-stationary but there are two types of non-stationary this is random walk and pure random walk random walk with trend only there is a trend but there is no random walk the value only depending on the time period with the passage of time it is changing the time when the value is deterministic trend to make it non-stationary the procedure will be different like if you have a pure random walk you can find the difference of the series if you take the difference then the random walk will be over and the series will be stationary and the unit will be over if there is a deterministic trend in your series with the passage of time the value is changing so you have to take the mean of every value of y if you take y minus y then we call it detrending if you have the trend of the series to eliminate that trend from every yt to yt bar minus then you will have a new series and we will call that series stationary as I have shared with you about the data of GDP and the data of GDP with the passage of time is increasing and when every value is increasing then we will not take the difference we will detrend it and when detrending is done then your non-stationary series will be converted into stationary and when we finish the deterministic trend then we call it the process of detrending that the trend has to be over and when the trend is over then we can call your series non-stationary to stationary or the unit root problem we resolved that problem by detrending the series and due to detrending your non-stationary series will be converted into stationary