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When using the Regression tools you cannot plot the points of your data and your model on the same graph?
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∙ 10y ago
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∙ 10y ago
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What is the difference between the logistic regression and regular regression?
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.
What is a linear graph?
A linear graph is a model of a straight line on the X and Y axis. It represents the equation y=mx+b. A liner graph has a slope. A liner graph cannot be equaled to 0.
What is the difference between classical regression analysis and spatial regression analysis?
how can regression model approach be useful in lean construction concept in the mass production of houses
What does f statistic mean?
The F-statistic is a test on ratio of the sum of squares regression and the sum of squares error (divided by their degrees of freedom). If this ratio is large, then the regression dominates and the model fits well. If it is small, the regression model is poorly fitting.
What can you conclude if the global test of regression does not reject the null hypothesis?
You can conclude that there is not enough evidence to reject the null hypothesis. Or that your model was incorrectly specified. Consider the exact equation y = x2. A regression of y against x (for -a < x < a) will give a regression coefficient of 0. Not because there is no relationship between y and x but because the relationship is not linear: the model is wrong! Do a regression of y against x2 and you will get a perfect regression!
What is residual in linear regression model?
You have a set of data points (x1,y1), (x2,y2), ..., (xn,yn), and you have assumed a line model, y = mx + b + e, where e is random error.You have fit the regression model to obtain estimates of the slope, m, and the intercept, b. Let me call them m and b.Now you can calculate yi - mxi - b for i = 1, 2, ... n. Notice that, for each i, this is an estimate of the error in yi. It's called the residual because it's what's 'left over' in yi after removing the part 'explained' by the regression.Another way of understanding this is to take a set of linearly related (x,y) pairs, graph them, calculate the regression line, plot it on the same graph and then measure the verticaldistances between the regression line and the each of the pairs. Those vertical distances are the residuals.
What is the difference between the logistic regression and regular regression?
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.
What is a measure of the explanatory power of the regression model?
Regression analysis describes the relationship between two or more variables. The measure of the explanatory power of the regression model is R2 (i.e. coefficient of determination).
What is a linear graph?
A linear graph is a model of a straight line on the X and Y axis. It represents the equation y=mx+b. A liner graph has a slope. A liner graph cannot be equaled to 0.
Where ridge regression is used?
Ridge regression is used in linear regression to deal with multicollinearity. It reduces the MSE of the model in exchange for introducing some bias.
What is the difference between classical regression analysis and spatial regression analysis?
how can regression model approach be useful in lean construction concept in the mass production of houses
What does f statistic mean?
The F-statistic is a test on ratio of the sum of squares regression and the sum of squares error (divided by their degrees of freedom). If this ratio is large, then the regression dominates and the model fits well. If it is small, the regression model is poorly fitting.
What is the difference between simple and multiple linear regression?
I want to develop a regression model for predicting YardsAllowed as a function of Takeaways, and I need to explain the statistical signifance of the model.
What does a large F-statistic mean?
The F-statistic is a test on ratio of the sum of squares regression and the sum of squares error (divided by their degrees of freedom). If this ratio is large, then the regression dominates and the model fits well. If it is small, the regression model is poorly fitting.
Can you obtain R-square from standardized regression model?
yes
How is linear regression used?
Linear regression can be used in statistics in order to create a model out a dependable scalar value and an explanatory variable. Linear regression has applications in finance, economics and environmental science.
What is the roll of p-value in regression analysis?
It is a measure of how likely the observed values (or those more extreme) are under the assumptions of the regression model.
