any proof??
The bookis of the 31.52 MB in size and this doesn't seem real for a genuine pdf.
Why not post the page 14 and 44 of the book here for an inspection?

14 INTRODUCTION
Table 1.13 Cost of Health Care
Row RURAL BED MCDAYS TDAYS PCREV NSAL FEXP NETREV
1 0 244 128 385 23521 5230 5334 12957
2 1 59 155 203 9160 2459 493 6208
3 0 120 281 392 21900 6304 6115 9481
4 0 120 291 419 22354 6590 6346 9418
5 0 120 238 363 17421 5362 6225 5834
6 1 65 180 234 10531 3622 449 6460
7 1 120 306 372 22147 4406 4998 12743
8 1 90 214 305 14025 4173 966 8886
9 0 96 155 169 8812 1955 1260 5597
10 1 120 133 188 11729 3224 6442 2063
11 0 62 148 192 8896 2409 1236 5251
12 1 120 274 426 20987 2066 3360 15561
13 0 116 154 321 17655 5946 4231 7478
14 1 59 120 164 7085 1925 1280 3880
15 1 80 261 284 13089 4166 1123 7800
16 1 120 338 375 21453 5257 5206 10990
17 1 80 77 133 7790 1988 4443 1359
18 1 100 204 318 18309 4156 4585 9568
19 1 60 97 213 8872 1914 1675 5283
20 1 110 178 280 17881 5173 5686 7022
21 0 120 232 336 17004 4630 907 11467
22 0 135 316 442 23829 7489 3351 12989
23 1 59 163 191 9424 2051 1756 5617
24 0 60 96 202 12474 3803 2123 6548
25 1 25 74 83 4078 2008 4531 -2461
26 1 221 514 776 36029 1288 2543 32198
27 1 64 91 214 8782 4729 4446 -393
28 0 62 146 204 8951 2367 1064 5520
29 1 108 255 366 17446 5933 2987 8526
30 1 62 144 220 6164 2782 411 2971
31 0 90 151 286 2853 4651 4197 -5995
32 0 146 100 375 21334 6857 1198 13279
33 1 62 174 189 8082 2143 1209 4730
34 1 30 54 88 3948 3025 137 786
35 0 79 213 278 11649 2905 1279 7465
36 1 44 127 158 7850 1498 1273 5079
37 0 120 208 423 29035 6236 3524 19275
38 1 100 255 300 17532 3547 2561 11424
39 1 49 110 177 8197 2810 3874 1513
40 1 123 208 336 22555 6059 6402 10094
41 1 82 114 136 8459 1995 1911 4553
42 1 58 166 205 10412 2245 1122 7045
43 1 110 228 323 16661 4029 3893 8739
44 1 62 183 222 12406 2784 2212 7410
45 1 86 62 200 11312 3720 2959 4633
46 1 102 326 355 14499 3866 3006 7627
47 0 135 157 471 24274 7485 1344 15445
48 1 78 154 203 9327 3672 1242 4413
49 1 83 224 390 12362 3995 1484 6883
50 0 60 48 213 10644 2820 1154 6670
51 1 54 119 144 7556 2088 245 5223
52 0 120 217 327 20182 4432 6274 9476

44 SIMPLE LINEAR REGRESSION
correlation coefficient between Y and Y, which is given by
(2.42)
where y is the mean of the response variable Y and 11 is the mean of the
fitted valu:s. In fact, the scatter plot of Y versus X and the scatter plot of
Y versus Y are redundant because the patterns of points in the two graphs
are identical. The two corresponding values of the correlation coefficient are
related by the following equation:
Cor(Y, Y) = ICor(Y, X) I. (2.43)
Note that Cor(Y, Y) cannot be negative (why?), but Cor(Y, X) can be positive
or negative [-1 ~ Cor(Y, X) ~ 1]. Therefore, in simple linear regression,
the scatter plot of Y versus Y is redundant. However, in multiple regression,
the scatter plot of Y versus Y is not redundant. The graph is very useful
because, as we shall see in Chapter 3, it is used to assess the strength of the
relationship between Y and the set of predictor variables Xl, X2,'" ,Xp,
4. Although scatter plots of Y versus Y and Cor(Y, Y) are redundant in simple
linear regression, they give us an indication of the quality of the fit in both
simple and multiple regression. Furthermore, in both simple and multiple
regressions, Cor(Y, Y) is related to another useful measure of the quality of
fit of the linear model to the observed data. This measure is developed as
follows. After we compute the least squares estimates of the parameters of a
linear model, let us compute the following quantities:
SST ~)Yi - y)2,
SSR ~)Yi - y)2, (2.44)
SSE = L)Yi - Yi)2,
where SST stands for the total sum of squared deviations in Y from its mean
y, SSR denotes the sum of squares due to regression, and SSE represents
the sum of squared residuals (errors). The quantities (Yi - V), (Yi - V), and
(Yi - Yi) are depicted in Figure 2.7 for a typical point (Xi, Yi). The line
Yi = /30 + /31 Xi is the fitted regression line based on all data points (not
shown on the graph) and the horizontal line is drawn at Y = y. Note that
for every point (Xi, Yi), there are two points, (Xi, Yi), which lies on the fitted
line, and (Xi, y) which lies on the line Y = y.
A fundamental equality, in both simple and multiple regressions, is given by
SST = SSR + SSE. (2.45)
This equation arises from the description of an observation as

extract the pages 14 and 44 of the book in pdf format. Let me see see!

Come on! Le's be frank your book is a scam.

keep it for free then. if it were scam it wouldn't copy paste here even.

this is not scanned copy. risk the one coin, and if you are not satisfied pls contact me for the refund. if you feel satisfied then pls fund me with the reward. thanks

or you can directly contact me through private message

This is a scanned ebook. I need  the latex version.

非常非常感谢