Results 201 to 210 of about 890,584 (243)
Some of the next articles are maybe not open access.
2011
The main purpose of this chapter is to predict the value of some variable Y based on a given set of variables X i where i = 1, 2, …, p − 1 and p is an integer larger than or equal to 2. The following example will be examined in detail throughout this chapter.
+4 more sources
The main purpose of this chapter is to predict the value of some variable Y based on a given set of variables X i where i = 1, 2, …, p − 1 and p is an integer larger than or equal to 2. The following example will be examined in detail throughout this chapter.
+4 more sources
2014
This chapter provides an overview of multiple linear regression, a statistical technique that predicts values of a quantitative dependent variable from values of two or more independent variables. By including more than one independent variable, a multiple linear regression can often account for more variability in the dependent variable than can a ...
William H. Holmes, William C. Rinaman
openaire +2 more sources
This chapter provides an overview of multiple linear regression, a statistical technique that predicts values of a quantitative dependent variable from values of two or more independent variables. By including more than one independent variable, a multiple linear regression can often account for more variability in the dependent variable than can a ...
William H. Holmes, William C. Rinaman
openaire +2 more sources
International Journal of Injury Control and Safety Promotion, 2018
Simple linear regression models study the relationship between a single continuous dependent variable Y and one independent variable X (Bangdiwala, 2018).
openaire +2 more sources
Simple linear regression models study the relationship between a single continuous dependent variable Y and one independent variable X (Bangdiwala, 2018).
openaire +2 more sources
2007
This chapter describes multiple linear regression, a statistical approach used to describe the simultaneous associations of several variables with one continuous outcome. Important steps in using this approach include estimation and inference, variable selection in model building, and assessing model fit.
openaire +2 more sources
This chapter describes multiple linear regression, a statistical approach used to describe the simultaneous associations of several variables with one continuous outcome. Important steps in using this approach include estimation and inference, variable selection in model building, and assessing model fit.
openaire +2 more sources
2017
Sie lernen in Erweiterung der Ihnen bekannten einfachen linearen Regression, wie man aus den Daten einer Stichprobe eine lineare funktionale Beziehung zwischen einem abhangigen Merkmal und mehreren unabhangigen Merkmalen gewinnt. Sie haben verstanden, dass die grundsatzlichen Uberlegungen ganz weitgehend analog zum Fall der einfachen Regression sind ...
Thomas Schuster, Arndt Liesen
openaire +1 more source
Sie lernen in Erweiterung der Ihnen bekannten einfachen linearen Regression, wie man aus den Daten einer Stichprobe eine lineare funktionale Beziehung zwischen einem abhangigen Merkmal und mehreren unabhangigen Merkmalen gewinnt. Sie haben verstanden, dass die grundsatzlichen Uberlegungen ganz weitgehend analog zum Fall der einfachen Regression sind ...
Thomas Schuster, Arndt Liesen
openaire +1 more source
1991
The multiple linear regression model is the most commonly applied statistical technique for relating a set of two or more variables. In Chapter 3 the concept of a regression model was introduced to study the relationship between two quantitative variables X and Y.
openaire +1 more source
The multiple linear regression model is the most commonly applied statistical technique for relating a set of two or more variables. In Chapter 3 the concept of a regression model was introduced to study the relationship between two quantitative variables X and Y.
openaire +1 more source
1987
The multiple linear regression model describes the relationship between a response variable y and a number of explanatory variables x1,…xp,p≥2. A multiple regression analysis is an analysis of a data set composed of n cases (yi,xi1,…xip), i=1,…,n, where each case consists of joint observations of the response variable and the explanatory variables as ...
Erling B. Andersen +2 more
openaire +1 more source
The multiple linear regression model describes the relationship between a response variable y and a number of explanatory variables x1,…xp,p≥2. A multiple regression analysis is an analysis of a data set composed of n cases (yi,xi1,…xip), i=1,…,n, where each case consists of joint observations of the response variable and the explanatory variables as ...
Erling B. Andersen +2 more
openaire +1 more source