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61) The results showed that the length of score vector in AMMI model was better to explain genotype by environment interaction than by joint linear regression model.

62) The sampling distribution and hypothesis testing of this non-linear generalized correlation coefficient will be studied with linear regression model .

63) The next step in the simple linear regression procedure is to determine if the remaining squared error of prediction is acceptable or not.

64) These are some of the more advanced topics awaiting the student of simple linear regression.

65) We use linear regression analyses to get coordinate conversion parameter and make the result is optimal.

66) Calculates the linear regression of a set and returns the coefficient of determination, R2.

67) We applied generalized linear regression analysis to control possible confounding factors related to explore the impact of numerical indicator variable factors.

68) Linear regression and artificial neural network usually used in the - variate calibration work in analytical chemistry.

69) A robust method based on linear regression for speech signal time delay estimation is presented and it is proved better performance than GCC method through experiment in the reverberant rooms.

70) This series has studied two applications of simple linear regression analysis.

71) The linear regression equation on the relationship between peroxide content in acrylonitrile and PAN fiber yellowness was obtained by regression analysis.

72) Methods Analyzing the Survival function of the original lifetime data(Sentencedict), and developing Linear Regression Equations by means of related analysis data.

73) It is very convenient for EXCEL, software of Microsoft Corporation, to solve the problem of one variable linear regression.

74) Multiple linear regression, binominal regression and neural network methods were applied in the analyses.

75) The grades were designed by equal space between logarithm, and the median lethal concentration was computed by Linear Regression.

76) Based on the absorbance data of a group, standard solution, working equation of component was established by linear regression.

77) With the method of linear regression, the paper discusses the factors associated with fitter's operation skill.

78) From a learning point of view, simple linear regression modeling is worth further study because it is arguably the gateway to understanding more advanced forms of statistical modeling.

79) Many of the core concepts from simple linear regression, for example, establish a good foundation for understanding Multiple Regression, Factor Analysis, Time Series, and so on.

80) To counter the problem of multiple linear regression in statistical forecast, we put forward the method that designs computer software and makes it come true.

81) The normal equation of linear regression is used to calculate the effects of high frequency components on the determination of secular trend of relative sea level(RSL).

82) A stepwise multiple linear regression analysis showed that HDL - C, FPG, WC , BF % enter the regression equation.

83) These transformations can linearize the data so that simple linear regression can be used to model the data.

84) This paper use experimental data to set up linear regression equation with unitary and regression straight line, To use variance analysis and related coefficient to test validity of equation.

85) Simple linear regression model is applied to compare the difference in SGA usage pattern between public and private hospitals.

86) I also demonstrated how to develop and implement the heart of a simple linear regression algorithm using PHP as the implementation language.

87) Trial-and-error method of the linear regression is introduced to determine the reasonable range of geological parameters. And the nonlinear least square method to calculate OGIP.

88) This paper gives weighted least squares estimate and the method to choose optimum weighted function for linear regression model.

89) In linear regression, the least squares estimation is heavily innuenced with outlyers.

90) Examples in this paper show that the dummy variable can draw some quality markers which is impossible to be quantized into the linear regression model.