Interpolation problems

[kwinisy]

hey guys. i am having problems with interpolation. our teacher taught the forecast method, but I tried applying it on my project it doesnt work. i mean the forecast method worked but the returned value isn't the right answer if you are to check in on a calculator.

	A	B
1	PRESSURE	0.12
2	TEMPERATURE

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i named the columns P and T so this is my formula
on cell b2 i entered "=IFERROR(VLOOKUP($B$1,P,FALSE),FORECAST($B$1, T,P)"
the returned value is 204.4886
but if you will compute it on a calculator the answer is 39.65
HOW CAN I IMPROVE THE FORMULA?

P(psia) T (⁰F) 0.0886 32 0.096 34 0.104 36 0.1125 38 0.1216 40 0.1314 42 0.1419 44 0.1531 46 0.1651 48 0.178 50 0.1916 52 0.2063 54 0.2218 56 0.2384 58 0.2561 60 0.2749 62 0.295 64 0.3163 66 0.3389 68 0.3629 70 0.3884 72 0.4155 74 0.4442 76 0.4746 78 0.5068 80 0.5409 82 0.577 84 0.6152 86 0.6555 88 0.6981 90 0.7431 92 0.7906 94 0.8407 96 0.8936 98 0.9462 100 1.0079 102 1.0697 104 1.1347 106 1.203 108 1.275 110 1.351 112 1.43 114 1.513 116 1.601 118 1.693 120 1.789 122 1.89 124 1.996 126 2.107 128 2.223 130 2.345 132 2.472 134 2.605 136 2.744 138 2.889 140 3.041 142 3.2 144 3.365 146 3.538 148 3.718 150 3.906 152 4.102 154 4.307 156 4.52 158 4.741 160 4.972 162 5.212 164 5.462 166 5.722 168 5.993 170 6.274 172 6.566 174 6.869 176 7.184 178 7.511 180 7.85 182 8.203 184 8.568 186 8.947 188 9.34 190 9.747 192 10.168 194 10.605 196 11.058 198 11.526 200 12.011 202 12.512 204 13.031 206 13.569 208 14.123 210 14.696 212 15.592 215 17.186 220 18.912 225 20.78 230 22.79 235 24.97 240 27.31 245 29.82 250 32.53 255 35.43 260 38.53 265 41.86 270 45.41 275 49.20 280 53.24 285 57.55 290 62.13 295 67.01 300 72.18 305 77.67 310 83.48 315 89.64 320 96.16 325 103.05 330 110.32 335 117.99 340 126.08 345 134.60 350 143.57 355 153.01 360 162.93 365 173.34 370 184.27 375 195.73 380 207.74 385 220.32 390 233.49 395 247.26 400 261.65 405 276.69 410 292.40 415 308.78 420 325.87 425 343.67 430 362.23 435 381.54 440 401.64 445 422.55 450 444.28 455 466.87 460 490.32 465 514.67 470 539.94 475 566.15 480 593.32 485 621.48 490 650.65 495 680.86 500 712.12 505 744.47 510 777.93 515 812.53 520 848.28 525 885.23 530 923.39 535 962.79 540 1003.5 545 1045.4 550 1088.7 555 1132.4 560 1179.4 565 1226.9 570 1275.8 575 1326.2 580 1378.1 585 1431.5 590 1486.6 595 1543.2 600 1601.5 605 1661.6 610 1723.3 615 1786.9 620 1852.2 625 1919.5 630 1988.7 635 2059.9 640 2133.1 645 2208.4 650 2285.9 655 2365.7 660 2398.2 662 2431.1 664 2464.4 666 2498.1 668 2532.2 670 2566.6 672 2601.5 674 2636.8 676 2672.5 678 2708.6 680 2745.1 682 2782.1 684 2819.5 686 2857.4 688 2895.7 690 2934.5 692 2973.7 694 3013.4 696 3053.6 698 3094.3 700 3135.5 702 3177.2 704 3208.2 705.47 <tbody> </tbody>

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[kwinisy]

the given table is in cells C1:D208

 

[shg]

FORECAST interpolates a linear trendline, and the data is not linear at all. This interpolates a monotone ascending series:

	C​	D​	E​	F​	G​	H​
1​	P(psia)​	T (⁰F)​	​	P​	T​	​
2​	0.089​	32​		0.12​	39.64823​	G2: =PERCENTILE($D$2:$D$205, PERCENTRANK($C$2:$C$205, F2, 6))
3​	0.096​	34​
4​	0.104​	36​
5​	0.113​	38​
6​	0.122​	40​
7​	0.131​	42​
8​	0.142​	44​
9​	0.153​	46​