Example sentences of "[vb mod] just have a [noun sg] at " in BNC.

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1 Let's , let's just have a look at what those phrases mean in plain Eng in plain English .
2 Now let's just have a look at some problem areas .
3 Let's just have a look at the dressing . ’
4 Let's just have a look at some of the statistics from that eventful first half and er an eye-catching one at the bottom there look fouls conceded twelve to Leicester four to Nottingham Forest .
5 Let's just have a look at this one again .
6 Let's just have a look at the erm , let's do the who 've we got , Bill ?
7 Before we move on , let's just have a look at those numerical estimates , can we look at the coefficients on income , notice that in this model because we 've logged both dependent and the independent variables , right , the coefficients that we estimate are elasticities , right , so we can read those coefficients off directly as elasticities and that 's the case for any model in which all the variables are logged right , in er , if we did n't log the data , in order to calculate the elasticity we have to multiply a coefficient the computer gives us by a erm price quantity ratio , price less , less part of the income constant ratio to obtain the income elasticities .
8 Right so the functional form test , if we look at the kie squared version , right , again we 've got a very small er test statistic implying there 's no breach of functional form right , the , the log er specification , right , seems to be working okay , there 's no problems with it erm if we now look at normality we 've got a bit of a problem with normality , right in that our test statistic is now four point nine , if we look at the critical value at the five percent level of kie when kie squared two , ah it 's not too bad , our five percent critical value of the kie squared two is five point nine nine , so although that test statistic is reasonably high , I mean you 'd probably reject , oh yes , we can reject the null at ten percent of normally distributed errors we would n't reject the null at five percent erm let's just have a look at in actual fact at those errors to see what the problem is .
9 Let's just have a look at what happens as we increase the lab , the labour output .
10 Let's just have a look at what you 've actually achieved .
11 Let's just have a look at them have you got the general conditions here ?
12 Now let's just have a look at what we 're doing .
13 Let's just have a look at your erm camera .
14 Right , let's just have a look at this other dress .
15 That 'll be , that 'll be alright , let's just have a look at the
16 Let's just have a look at if we 've got six and four we can have six plus four or you can have six minus four we can have minus six , minus four or you can have minus six plus four .
17 Erm we 'll just have a look at what we 've got .
18 Right , if you just want to come out of there and we 'll just have a look at the plot of the residuals , if you plot the residuals the test for serial correlation there well the test for serial correlation , right , and try and determine whether there 's a auto regressive structure to those parameters and I think Steve was talking to you about er auto regressions , so what the computer is doing essentially , it is getting the residuals from the model raised and it 's regressing them right on the residuals in the previous period , right , and it 's testing whether this parameter row , right , is significantly different from zero right , now if this is , if row is significantly different from zero , let's say it 's nought point six , that implies the residuals in T are not independent of the residuals in T minus one .
19 I 'll just have a look at these shirts up here no , they 're nice Bev
20 Well what we 'll do is we 'll do , we 'll just have a pump at the side of the till .
21 I 'll just have a shot at pencilling that in .
22 Perhaps we could just have a look at what sort of angles we 've got here .
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