Диссертация (1172916), страница 18
Текст из файла (страница 18)
TheDurbin-Watson (DW) statistic tests the residuals to determine if there is any significant correlationbased on the order in which they occur in your data file. Since the P-value is less than 0,05, there isan indication of possible serial correlation at the 95,0 % confidence level. Plot the residuals versusrow order to see if there is any pattern that can be seen.129Таблица А.3 – Результаты обработки экспериментальных данных по изменениюудельной теплоемкости образцов из ФТБ от температурыDependent variable: cp = f(T)ParameterInterceptSlopeEstimate339,72726,9526Standard Error40,72221,45209T Statistic8,3425518,5613P-Value0,00000,0000Analysis of VarianceSourceModelResidualTotal (Corr.)Sum of Squares406349,012974,1419323,0Df11112Mean Square406349,01179,46F-Ratio344,52P-Value0,0000Correlation Coefficient = 0,984408R-squared = 96,9059 percentR-squared (adjusted for d.f.) = 96,6247 percentStandard Error of Est.
= 34,3433Mean absolute error = 23,8876Durbin-Watson statistic = 1,26079 (P = 0,0355)Lag 1 residual autocorrelation = 0,121685The StatAdvisorThe output shows the results of fitting a linear model to describe the relationship betweenсp and T . The equation of the fitted model isc p 339,727 26,9526 T .Since the P-value in the ANOVA table is less than 0,05, there is a statistically significantrelationship between cp and T at the 95,0 % confidence level.The R-Squared statistic indicates that the model as fitted explains 96,9059 % of the variabilityin cp.
The correlation coefficient equals 0,984408, indicating a relatively strong relationshipbetween the variables. The standard error of the estimate shows the standard deviation of theresiduals to be 34,3433. This value can be used to construct prediction limits for new observationsby selecting the Forecasts option from the text menu.The mean absolute error (MAE) of 23,8876 is the average value of the residuals. The DurbinWatson (DW) statistic tests the residuals to determine if there is any significant correlation based onthe order in which they occur in your data file.
Since the P-value is less than 0,05, there is an indication of possible serial correlation at the 95,0 % confidence level. Plot the residuals versus row orderto see if there is any pattern that can be seen.130Таблица А.4 – Результаты обработки экспериментальных данных по изменениюкоэффициента теплопроводности образцов из ФТБ от температурыDependent variable: λ = f(T)ParameterInterceptSlopeEstimate0,65736420,3004Standard Error0,01690521,31277T Statistic38,885315,4638P-Value0,00000,0000Analysis of VarianceSourceModelResidualTotal (Corr.)Sum of Squares0,63051100,02900360,659515Df11112Mean Square0,630511000,00263669F-Ratio239,13P-Value0,0000Correlation Coefficient = 0,977764R-squared = 95,6023 percentR-squared (adjusted for d.f.) = 95,2025 percentStandard Error of Est. = 0,0513487Mean absolute error = 0,0347007Durbin-Watson statistic = 1,11069 (P = 0,0205)Lag 1 residual autocorrelation = 0,406608The StatAdvisorThe output shows the results of fitting a reciprocal-Y logarithmic-X model to describe therelationship between λ and f(T).
The equation of the fitted model isλ 0,66 20,3 / (T 273).Since the P-value in the ANOVA table is less than 0,05, there is a statistically significantrelationship between λ and f(T) at the 95,0 % confidence level.The R-Squared statistic indicates that the model as fitted explains 97,4446 % of the variabilityin λ. The correlation coefficient equals 0,98714, indicating a relatively strong relationship betweenthe variables. The standard error of the estimate shows the standard deviation of the residuals to be0,11062. This value can be used to construct prediction limits for new observations by selecting theForecasts option from the text menu.The mean absolute error (MAE) of 49716,8 is the average value of the residuals. The DurbinWatson (DW) statistic tests the residuals to determine if there is any significant correlation based onthe order in which they occur in your data file.
Since the P-value is less than 0,05, there is an indication of possible serial correlation at the 95,0 % confidence level. Plot the residuals versus row orderto see if there is any pattern that can be seen.131Таблица А.5 – Результаты обработки экспериментальных данных по изменениюплотности образцов из ТБ от температурыDependent variable: ρ = f(T)ParameterCONSTANTTT2Estimate2119,91-0,4634880,000204428Standard Error7,301880,03333470,0000299568T Statistic290,324-13,90416,82411P-Value0,00000,00000,0000Analysis of VarianceSourceModelResidualTotal (Corr.)Sum of Squares103202,01251,84104454Df21012Mean Square51600,9125,184F-Ratio412,20P-Value0,0000R-squared = 98,8015 percentR-squared (adjusted for d.f.) = 98,5618 percentStandard Error of Est.
= 11,1885Mean absolute error = 7,3902Durbin-Watson statistic = 1,20355 (P = 0,0086)Lag 1 residual autocorrelation = 0,369666The StatAdvisorThe output shows the results of fitting a second order polynomial model to describe therelationship between ρ and f(T). The equation of the fitted model isρ = 2119,91 – 0,46(Т – 273) + 0,0002(Т – 273)2.Since the P-value in the ANOVA table is less than 0,05, there is a statistically significantrelationship between ρ and f(T) at the 95 % confidence level.The R-Squared statistic indicates that the model as fitted explains 98,8015 % of thevariability in ρ.
The adjusted R-squared statistic, which is more suitable for comparing models withdifferent numbers of independent variables, is 98,5618 %. The standard error of the estimate showsthe standard deviation of the residuals to be 11,1885. This value can be used to construct predictionlimits for new observations by selecting the Forecasts option from the text menu. The mean absoluteerror (MAE) of 7,3902 is the average value of the residuals. The Durbin-Watson (DW) statistic teststhe residuals to determine if there is any significant correlation based on the order in which theyoccur in your data file. Since the P-value is greater than 0,05, there is no indication of serial autocorrelation in the residuals at the 95 % confidence level.In determining whether the order of the polynomial is appropriate, note first that the P-valueon the highest order term of the polynomial equals 0,0000460223.
Since the P-value is less than 0,05,the highest order term is statistically significant at the 95 % confidence level. Consequently,you probably don't want to consider any model of lower order.132Таблица А.6 – Результаты обработки экспериментальных данных по изменениютемпературопроводности образцов из ТБ от температурыDependent variable: a = f(T)ParameterInterceptSlopeEstimate-0,05669060,49339Standard Error0,1617250,0273801T Statistic-0,35053718,02P-Value0,73260,0000Analysis of VarianceSourceModelResidualTotal (Corr.)Sum of Squares4,261330,1443544,40569Df11112Mean Square4,261330,0131231F-Ratio324,72P-Value0,0000Correlation Coefficient = 0,983481R-squared = 96,7235 percentR-squared (adjusted for d.f.) = 96,4256 percentStandard Error of Est.
= 0,114556Mean absolute error = 0,0861908Durbin-Watson statistic = 0,851316 (P = 0,0031)Lag 1 residual autocorrelation = 0,431034The StatAdvisorThe output shows the results of fitting a reciprocal-Y logarithmic-X model to describe therelationship between a and f(T). The equation of the fitted model isa = 1/(–0,056 + 0,49ln(T – 273)).Since the P-value in the ANOVA table is less than 0,05, there is a statistically significantrelationship between a and f(T) at the 95,0 % confidence level.The R-Squared statistic indicates that the model as fitted explains 96,7235 % of the variabilityin a.
The correlation coefficient equals 0,983481, indicating a relatively strong relationship betweenthe variables. The standard error of the estimate shows the standard deviation of the residuals to be0,114556. This value can be used to construct prediction limits for new observations by selecting theForecasts option from the text menu.The mean absolute error (MAE) of 0,0861908 is the average value of the residuals.
TheDurbin-Watson (DW) statistic tests the residuals to determine if there is any significant correlationbased on the order in which they occur in your data file. Since the P-value is less than 0,05, there isan indication of possible serial correlation at the 95,0 % confidence level. Plot the residuals versusrow order to see if there is any pattern that can be seen.133Таблица А.7 – Результаты обработки экспериментальных данных по изменениюудельной теплоемкости образцов из ТБ от температурыDependent variable: cp = f(T)ParameterInterceptSlopeEstimate440,56332,6772Standard Error57,50972,0507T Statistic7,6606915,9347P-Value0,00000,0000Analysis of VarianceSourceModelResidualTotal (Corr.)Sum of Squares597293,025875,9623169,0Df11112Mean Square597293,02352,35F-Ratio253,91P-Value0,0000Correlation Coefficient = 0,979018R-squared = 95,8477 percentR-squared (adjusted for d.f.) = 95,4702 percentStandard Error of Est.
![](https://s.studizba.com/z.php?f=/templates/si/i/noavatar.png&w=100&h=100&t=1"){kind=avatar}
