1) Linear regression was used for comparison with different variables.

2) The graph is a linear regression of.

3) We chose linear regression for describing the overall changes in mean sperm concentrations, but other statistical models have also been tested.

4) Table V shows results of stepwise multiple linear regression analysis of outcome variables from the ventilated infants.

5) Linear regression, for example, requires all the data to be collected ahead of time and then processed all at once.

6) Using multiple linear regression analysis, gastritis with atrophy was the only factor that had an independent negative effect on acid secretion.

7) Shared care did not contribute to the multiple linear regression model.

8) A multiple linear regression model was used to assess the independent effects on diabetic control of those variables studied.

9) Correlation studies were performed using linear regression and Spearman's correlation coefficients were calculated.

10) Linear Regression with Transformations of the dependent variable.

11) Simple linear regression is also a versatile modeling technique.

12) Multiple linear regression is used extensively in prediction.

13) Examples of neural coding. Simple linear regression.

14) Path analysis is the standardized linear regression analysis.

15) And I would ban linear regression.

16) Including: selection of core indicators, calculate indicators'weights, linear regression,(http:///linear regression.html) classification index level.

17) In this paper, an inputoutput incremental simple linear regression model is used as a predictive model of black box systems, and a projection algorithm is adopted to estimate the model parameters.

18) And the equation of bivariate linear regression between frost heaving ratio and content, compactness is established.

19) Respiratory symptoms were analysed by multiple logistic regression and lung function standard deviation scores by multiple linear regression.

20) Each patient had three measurements of bone mineral density and rates of bone loss were estimated by linear regression for each subject.

21) To investigate relations between sets of possible explanatory factors and each outcome variable a stepwise multiple linear regression analysis was used.

22) Time trends and age at diagnosis were evaluated with a linear regression model by the method of least squares.

23) Two mathematical models of bluish dogbane textile processing were set up by single variable linear regression analysis: one is for the mass of No.

24) Before you plunge into learning more advanced techniques, like multiple regression or manova, you could benefit from having a solid understanding of simple linear regression.

25) Quatitative structure - activity relationship models were constructed by multiple linear regression method.

26) Results were analyzed using t tests, analysis of variance and linear regression.

27) Most often the Genco has an in-house price forecast tool based on available forecasting methods such as the conventional linear regression analysis technique, to cater to the need of a price forecast.

28) The relationship between the Brix and the total soluble sugar content of sweet sorghum stalk juice was determined through one-dimensional linear regression.

29) It proposes an adaptive process scheduling approach based on the curvilinear regression that can be transformed to a linear regression.

30) Methods The measured body parameters and polysomnography(PSG)parameters of 155 patients with OSAHS entered into multiple linear regression analysis to correlate with apnea hyponea index (AHI).

31) Indicators of the bumper close planting tea orchard can be obtained from linear regression equation.

32) The data were analyzed by broad linear regression to carry the single factor and multifactorial analysis.

33) Also the linear regression equation between a cumulative temperature and duration was obtained.

34) This paper deals with the quantitative relations between regression coefficients and partial correlation coefficients in multivariate linear regression, and their statistical meanings.

35) For that, this paper gives a new characteristic index: time serial's Simple Linear regression Coefficient (SLC), this index is mainly used for the long time serial remote sensing image classification.

36) The data collected were described and analyzed with statistical description, t-test, analysis of variance , linear correlation and multiple linear regression.

37) Accordingly,() the end for multiple regression as against linear regression appeared quite reasonable.

38) Multiple linear regression and F-test were used to reveal the influence of sintering process parameters on the average speed at each forefront, and their relationships were proposed.

39) SECRET is a new algorithm for scalable linear regression trees.

40) There exist many problems for the logarithm linear regression formulations during estimating the cost of airborne avionics system.

41) The statistical methods used are general statistical description (such as mean and standard deviation), repetitive measurement deviation analysis, clustering analysis and multiple linear regression.

42) Methods: The risk factors were analyzed with multiple linear regression.

43) Multiwavelength - derivative method and linear regression spectrophotometry combined with least square method are applied to the simultaneous determination of NO_3 and NO_2 in water.

44) Methods Measure the depth of the soft tissue in the back neck of fetus, Biparietal diameter(BPD) , femur length(FL) and abdominal circumference(AC), and apply linear regression equation.

45) In this paper, an evaluation model is set up by utilizing statistical linear regression model method.

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

47) We avoid the interfere of different elements with the multiple linear regression gamma-ray detector.

48) And the quantitative relation is gained by the one dimension linear regression.

49) First order linear regression that automatically provides error calculations and graphic visualization.

50) Multiple linear regression and correlative analysis showed that the increase in optic axis was main factor for the formation of simple myopia of teenager.

51) The linear regression referred in the data preprocess strengthen the tide movement.

52) Methods Dummy variable is introduced into the linear regression equation to correct cyclical variation and reduce error of forecasting.

53) The main statistical methods were analysis of variance (ANOV A), multiple comparison, nonparametric test, t-test, linear regression and correlation and X2 test.

54) The sixth part forecasts the future logistics demand of Shandong Province on the basis of one linear regression, polynomial regression, gray system G(1,1) model and combination forecast model.

55) Students will focus on decision analysis, forecasting techniques, linear regression, project scheduling, queuing theory, and linear programming.

56) The statistical fractal features of the original coarse terrain data set were determined through linear regression, based on which a denser terrain can be derived by means of bilinear interpolation.

57) Next use factor analysis and multiple linear regression to exam the factors which influence on salesperson"s performance."

58) The basic goal behind simple linear regression modeling is to find the line of best fit through a two-dimensional plane of paired X and Y values (that is, your X and Y measurements).

59) Though the linear regression equation, grafting yield of product can be counted directly by contact angle.

60) The quasi-static input-output linear regression equation of the measuring system is established, and the testing results of input-output curve linearity and sluggishness are given.

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.

91) In this paper we shall discuss two topics: the empirical distribution function of censored data and the Linear regression with censored data.

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

93) Solutionmultiple linear regression equations, industrial control algorithm. Can be transplanted to MFC program.

94) The distribution of powder clusters of finely ground slag was measured by means of laser granulometer and was modeled through RRSB linear regression.

95) Discuss the means of deducing bidding models by linear regression and curve fit method, and further more( ), acquire rivals' bidding competitive ratio with fuzzy forecasting technique.

96) Multi-variety linear regression program is compiled using the least square method and the Gaussian elimination.

97) We avoid the interfere of different elements with the multiple linear regression Gamma - ray detector.

98) Specific analytical methods have linear regression analysis method and logic dichotomy.

99) Multiple Linear Regression complete source code can be used directly.

100) The empirical study part contains assumptions, description of statistical analysis, parameter testing of single-factor analysis of variance, correlation and multiple linear regression analysis.

101) In the first of this two-part series, " Simple linear regression with PHP," I explained why a math library can be useful for PHP.

102) And based on this, a simple method for performance prediction by using linear regression analysis is put forward.

103) Indeed, using basic tools like simple linear regression initially is a good way to begin probing data for patterns.