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The answer may be obtained from the SPSS manual. It is not realistic to try to explain it here.

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Q: How you can run multiple regression analysis with more than 4 independent variables through spss?
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Multiple regression analysis examines the relationship of several dependent variables on the independent variable?

True.


Simple regression and multiple regression?

Simple regression is used when there is one independent variable. With more independent variables, multiple regression is required.


Can dummy variables be used in multiple linear regression analysis?

Yes they can.


Can independent variables be changed?

Yes. In fact, in multiple regression, that is often part of the analysis. You can add or remove independent variables to the model so as to get the best fit between what values are observed for the dependent variable and what the model predicts for the given set of independent variables.


How do I perform regression analysis in SPSS?

To perform regression analysis in SPSS: Open your dataset in SPSS. Go to "Analyze" > "Regression." Select the type of regression analysis (linear or multiple). Move the dependent variable to the "Dependent" box. Move independent variables to the "Independent(s)" box. Optionally, specify additional settings. Click "OK" to run the analysis. Interpret the results in the generated output. You can take professional help also. Experts can surely help you and assist you in performing such data analysis tasks.


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 collinear in statistics?

Two or more explanatory variables are collinear when they have a linear relationship with each other. You are usually expected to remove at least one of the variables from your multiple regression analysis.


What is the difference between multiple regression and logistic regression?

In cases wherethe dependent variable can take any numerical value for a given set of independent variables multiple regression is used.But in cases when the dependent variable is qualitative(dichotomous,polytomous)then logistic regression is used.In Multiple regression the dependent variable is assumed to follow normal distribution but in case of logistic regression the dependent variablefollows bernoulli distribution(if dichotomous) which means it will be only0 or 1.


When you introduce more than one independent variable into a linear regression analysis?

Generally, when the dependent variable appears to be the result of more than one independent variables, a multiple regression model may be suitable. It is difficult to justify adding an additional variable, that does not significantly reduce the residual error of the fit. The setting of thresholds to justify addition of variables is in the area of "stepwise regression." The data must be adequate and consistent with the assumption of independent variables. I note from the first related link: Most authors recommend that one should have at least 10 to 20 times as many observations (cases, respondents) as one has variables, otherwise the estimates of the regression line are probably very unstable and unlikely to replicate if one were to do the study over. See related links. Many more are available in the Internet. Also, many books have been written on the multiple regression- proper and improper use.


What is the importance of correlation and regression analysis in business decision making?

Correlation and regression analysis can help business to investigate the determinants of key variables such as their sales. Variations in a companies sales are likely to be related to variation in product prices,consumers,incomes,tastes and preference's multiple regression analysis can be used to investigate the nature of this relationship and correlation analysis can be used to test the goodness of fit. Regression can also be used to estimate the trend in a time series to make forecast


What is multiple regression?

Statistical analysis that describes the changes in a dependent variable, such as sunglass sales volumes, associated with changes in one or more independent variables, such as the average age of the residents of a market area. For example, a multiple-regression analysis might reveal a positive relationship between demand for sunglasses and various demographic characteristics (age, income) of the buyers-that is, demand varies directly with changes in their characteristics. Multiple regression thereby helps marketers to identify their best prospects.For the source and more detailed information concerning this subject, click on the related links section (Answers.com) indicated below.


How can correlation and regression analysis be used to make strategic decisions in a dynamic competitive business environment filled with risk and uncertainty.?

Correlation and regression analysis can help business to investigate the determinants of key variables such as their sales. Variations in a companies sales are likely to be related to variation in product prices,consumers,incomes,tastes and preference's multiple regression analysis can be used to investigate the nature of this relationship and correlation analysis can be used to test the goodness of fit. Regression can also be used to estimate the trend in a time series to make forecast