Frequent question: Which of the following techniques is used to predict the value of one variable on the basis of other variables?

Which of the following techniques is used to predict the value of one variable on the basis of other variables? Regression analysis.

Which of the following statistical techniques uses values of more than one variable to predict the value of another variable?

Multiple linear regression (MLR), also known simply as multiple regression, is a statistical technique that uses several explanatory variables to predict the outcome of a response variable. Multiple regression is an extension of linear (OLS) regression that uses just one explanatory variable.

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Which of the following statistical techniques predicts or explains the value for a dependent variable using the values of independent variables?

Regression analysis is widely used for prediction and forecasting. Regression analysis is also used to understand which among the independent variables is related to the dependent variable, and to explore the forms of these relationships.

What is the name of the variable that is predicted by another variable?

The other name for the dependent variable is the Predicted variable(s). The dependent variables are named as such because they are the values that are predicted or assumed by the predictor / independent variables.

What statistical technique is used to explain the variance in the outcome variable based on the differences in the predictor variable?

Regression can be used to predict a value for the dependent variable for any value of the independent (i.e., predictor) variable(s). It can also be used to tell you how of the variance in the dependent variable is explained by the predictor variable(s).

Which method is used to predict the value of response variable from one or more predictor variables where the variables are numeric?

When analysts and researchers use the term regression by itself, they are typically referring to linear regression; the focus is usually on developing a linear model to explain the relationship between predictor variables and a numeric outcome variable.

What statistical technique is used to make predictions?

Regression analysis is a statistical technique for determining the relationship between a single dependent (criterion) variable and one or more independent (predictor) variables. The analysis yields a predicted value for the criterion resulting from a linear combination of the predictors.

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Which of the following is a statistical technique used to identify a correlation?

Factor analysis is a method used to determine variables that can explain the patterned correlations among the observed variables. Get to know more about this statistical method and its two types: confirmatory factor analysis and explanatory factor analysis.

Which one of the following statistical technique is used for multivariate analysis?

Multiple regression is the most commonly utilized multivariate technique. It examines the relationship between a single metric dependent variable and two or more metric independent variables.

Which of the following is a statistical technique used to determine the degree to which two variables are related?

=> The statistical technique used to determine the degree of relationship between two variables is called Correlation.

What will be the modeling technique used to predict a categorical variable?

Which technique is used to predict categorical responses? Classification methods are used to predict binary or multi class target variable.

Which of the following variable is being explained or predicted in a regression analysis?

dependent variable. The variable which we are trying to predict in a regression analysis is…

What is the variable which is the variable that is being predicted in the regression analysis?

Linear regression models are used to show or predict the relationship between two variables or factors. The factor that is being predicted (the factor that the equation solves for) is called the dependent variable.

What is one-way Anova used for?

One-Way ANOVA (“analysis of variance”) compares the means of two or more independent groups in order to determine whether there is statistical evidence that the associated population means are significantly different.

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What is ANOVA used for?

Like the t-test, ANOVA helps you find out whether the differences between groups of data are statistically significant. It works by analyzing the levels of variance within the groups through samples taken from each of them.

What is chi square test used for?

A chi-square test is a statistical test used to compare observed results with expected results. The purpose of this test is to determine if a difference between observed data and expected data is due to chance, or if it is due to a relationship between the variables you are studying.