Example sentences of "[pron] [modal v] [verb] t " in BNC.
Next page| No | Sentence |
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| 1 | I 'll swear t ’ that . ’ |
| 2 | I said it 's okay I just erm you know , I do n't I 'll probably , I 'm fine on my own , I 've got things to do and I can watch T V and I |
| 3 | One is to include corporate dummy variable of the intercept and see whether it 's T ratio or significantly different , is , sorry it 's greater than two right or we can use an F test , right , now that F test that 's given me that formula in the middle of the page is a very important test which was developed by a chap called Chow and as a result it become known as the Chow test and it 's a , it 's a test for parameter constancy , er do we have constant parameters in our model now it tells you how to compute this Chow test , in this particular case we 're only dummying the intercept , the Chow test gives exactly the same results of T tests , right , erm we wo n't bother going through it , if you want to go through this er sheet in your own time calculate that , that Chow test and essentially what it involves is splitting with the s the whole sample now into two sub-samples , right , the first sub-sample , right , is peacetime , the second sub-sample wartime , right , and you just compare the residual sum of the squares on the unaccounted for variation , right , between actual and fitted values , just compare the residual sum of squares between these two sub periods , right and if you use the formula that 's given there that will come out with exactly the same result , well in actual fact you can square , if you square the F statistic you get calculating one formula you will get T value , got from er the computer right , the er , the sheet goes on to say how we can er use dummy variables in slightly more complicated ways , right , we could see actually see whether the income or price elasticities of demand changed . |
| 4 | One of these , which we will call T A , contains node 1 . |
| 5 | Using the parametric programming procedure of Section 6.3 , we can connect T to T by a sequence of tableaux , each obtained by pivoting from its predecessor . |