PROBLEMS 1. Fit the following data in a linearly regressed line. Find the standard deviation. 0.1 0.2 0.3 0.5 0.7 0.16 0.32 0.56 0.84 2.0 2. Fit the following data in a linear regression line. Find...


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PROBLEMS<br>1. Fit the following data in a linearly regressed line. Find the standard deviation.<br>0.1<br>0.2<br>0.3<br>0.5<br>0.7<br>0.16<br>0.32<br>0.56<br>0.84<br>2.0<br>2. Fit the following data in a linear regression line. Find the standard error of estimate.<br>0.4<br>1, s<br>i, 10-3 Al0.2 0.3683 0.3819 0.2282 0.0486 0.0082 0.1441<br>0.2<br>0.4<br>0.6<br>0.8<br>1.2<br>3. Using the following data by linear interpolation, find the temperature at y = 2 cm.<br>3<br>5<br>у, ст<br>T, K<br>900<br>480<br>270<br>200<br>4. Fit the following data in a second order linear interpolation polynomial.<br>3<br>Y, cm<br>T, K<br>900<br>480<br>270<br>5. Fit the following data in a linearly regressed line. Find the co-efficient of variation.<br>X, cm<br>2<br>4<br>5<br>7 10<br>1, mm<br>2<br>1.35<br>1.34<br>1.6<br>1.58<br>1.42<br>Page 1 of 1<br>

Extracted text: PROBLEMS 1. Fit the following data in a linearly regressed line. Find the standard deviation. 0.1 0.2 0.3 0.5 0.7 0.16 0.32 0.56 0.84 2.0 2. Fit the following data in a linear regression line. Find the standard error of estimate. 0.4 1, s i, 10-3 Al0.2 0.3683 0.3819 0.2282 0.0486 0.0082 0.1441 0.2 0.4 0.6 0.8 1.2 3. Using the following data by linear interpolation, find the temperature at y = 2 cm. 3 5 у, ст T, K 900 480 270 200 4. Fit the following data in a second order linear interpolation polynomial. 3 Y, cm T, K 900 480 270 5. Fit the following data in a linearly regressed line. Find the co-efficient of variation. X, cm 2 4 5 7 10 1, mm 2 1.35 1.34 1.6 1.58 1.42 Page 1 of 1

Jun 05, 2022
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