I've included links to both these terms. Definitions from these links are given below. Correlation and regression are frequently misunderstood terms. Correlation suggests or indicates that a linear relationship may exist between two random variables, but does not indicate whether X causes Yor Y causes X. In regression, we make the assumption that X as the independent variable can be related to Y, the dependent variable and that an equation of this relationship is useful. Definitions from Wikipedia: In probability theory and statistics, correlation (often measured as a correlation coefficient) indicates the strength and direction of a linear relationship between two random variables. In statistics, regression analysis refers to techniques for the modeling and analysis of numerical data consisting of values of a dependent variable (also called a response variable) and of one or more independent variables (also known as explanatory variables or predictors). The dependent variable in the regression equation is modeled as a function of the independent variables, corresponding parameters ("constants"), and an error term. The error term is treated as a random variable. It represents unexplained variation in the dependent variable. The parameters are estimated so as to give a "best fit" of the data. Most commonly the best fit is evaluated by using the least squares method, but other criteria have also been used.
regression testing is a white box testng
how can regression model approach be useful in lean construction concept in the mass production of houses
A regression test is a test where a previously known bug is tested for after a change. A retest is simply repeating a test.
in general regression model the dependent variable is continuous and independent variable is discrete type. in genral regression model the variables are linearly related. in logistic regression model the response varaible must be categorical type. the relation ship between the response and explonatory variables is non-linear.
There is no corelation between a cylinders ID to OD.
diferece between ratio and regression
What is the difference between the population and sample regression functions? Is this a distinction without difference?
regression testing is a white box testng
how can regression model approach be useful in lean construction concept in the mass production of houses
yes
A regression test is a test where a previously known bug is tested for after a change. A retest is simply repeating a test.
in general regression model the dependent variable is continuous and independent variable is discrete type. in genral regression model the variables are linearly related. in logistic regression model the response varaible must be categorical type. the relation ship between the response and explonatory variables is non-linear.
applications of carl Pearson coefficient of corelation applications of carl Pearson coefficient of corelation applications of carl Pearson coefficient of corelation applications of carl Pearson coefficient of corelation applications of carl Pearson coefficient of corelation applications of carl Pearson coefficient of corelation
correlation we can do to find the strength of the variables. but regression helps to fit the best line
There is no corelation between amps and hertz
Positive correlation means that, if something increases, a factor dependent on it also increases. However, if there is negative correlation, the dependent factor decreases.
Ah, the stochastic error term and the residual are like happy little clouds in our painting. The stochastic error term represents the random variability in our data that we can't explain, while the residual is the difference between the observed value and the predicted value by our model. Both are important in understanding and improving our models, just like adding details to our beautiful landscape.