linear regression analysis

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linear regression analysis

a statistical method that aims to define the relationship between two variables, producing a value b, the regression coefficient. There are several assumptions that have to be made in carrying out the analysis, particularly

that there is an independent variable x, e.g. time, which can be measured exactly, and also a dependent variable y, e.g. metabolic rate,
that for every value of x there is a ‘true’ value of y . Linear regression analysis enables the fitting of a straight line to a scatter graph, using the equation y = a + bx, the a value being the point at which the regression line crosses the y -axis (the intercept).

Collins Dictionary of Biology, 3rd ed. © W. G. Hale, V. A. Saunders, J. P. Margham 2005

References in periodicals archive ?

Prediction of body weight from testicular and morphological characteristics in indigenous Mengali sheep of Pakistan: Using factor analysis scores in multiple linear regression analysis. Int.

Use of Factor Scores in Multiple Regression for Predicting Live Weight in Indigenous Savak Akkaraman Lambs

Table 1: Linear regression analysis of ISMI and quality of life.

Internalized Stigma, Quality of Life and Self Esteem in Chronic Schizophrenic Patients

Multiple linear regression analysis indicated that LVEF, calcified plaque and LDL-C were independent risk factors of multi-vessel coronary artery lesion of old CHD patients (P<0.05), which is consistent with previous research findings.22

Study on correlation between property of coronary artery lesion and degree of coronary artery stenosis of elderly patients with coronary heart disease

Table 1 reports multiple linear regression analysis of composite FMS and individual FMS elements as a predictor of [PL.sub.Total], [PL.sub.MLTotal], [PL.sub.APTotal], and [PL.sub.VTotal].

Functional Movement Screening as a Predictor of Mechanical Loading and Performance in Dancers

Table 2 showed results of linear regression analysis to predict quality of life from social acceptance.

EFFECT OF SOCIAL ACCEPTANCE ON QUALITY OF LIFE AMONG ORTHOPEDICALLY DISABLED STUDENTS FROM INCLUSIVE AND SPECIAL INSTITUTES

Hierarchical linear regression analysis among respondents with negative family-supportive organization perception (N = 96)-criterion: life satisfaction Model 4 B SE [beta] t 95% CI for B Constant 3.558 0.739 4.812*** 2.086-5.029 Marriage 0.014 0.010 0.171 1.420 -0.006-0.033 duration Number of -0.211 0.163 -0.159 -1.295 -0.536-0.113 children Commitment Parental -0.057 0.091 -0.081 -0.624 -0.238-0.124 role marital 0.060 0.104 0.075 0.573 -0.148-0.267 role occupational 0.320 0.124 0.282 2.573* 0.073-0.568 role Model 4--the last regression model in the analysis containing all study variables.

LIFE ROLE SALIENCE AND SUBJECTIVE WELL-BEING AMONG MACEDONIAN EMPLOYEES: DOES FAMILY-SUPPORTIVE ORGANIZATION PERCEPTION MODERATE THIS RELATIONSHIP

Multiple linear regression analysis showed that BMI was the main independent predictor for systolic and diastolic blood pressure (DBP).

Prevalence of hypertension and its risk factors in a field practice area of tertiary care teaching hospital in rural area of Western Maharashtra

After the measurements, linear regression analysis was done using cut perpendicularity as dependent variable and laser power P, cutting speed v and assist gas pressure p as independent variables.

Estimation of the Laser Cut Perpendicularity Using Linear Regression Analysis

After identifying various components of window systems that are believed to influence thermal performance of window systems, in this study, a multiple linear regression analysis was conducted to investigate the extent of the effects of those components on Upvalue.

Analysis of Window Components Affecting U-Value Using Thermal Transmittance Test Results and Multiple Linear Regression Analysis

For Multiple Linear Regression Analysis, the following constants were obtained:

Depth and Lineament Maps Derived from North Cameroon Gravity Data Computed by Artificial Neural Network

IA maintained stable with age in both genders (linear regression analysis: t = 0.56, P > 0.05 in male; t = 0.053, P > 0.05 in female).

Internal Astigmatism and Its Role in the Growth of Axial Length in School-Age Children

Variables with the highest [r.sup.2] value in relation to actual weight were then used in our linear regression analysis (P <0.05).

Development of a weight-estimation model to use in pregnant criollo-type mares/Modelo para estimativa de peso em eguas gestantes mesticas crioulas