Why Stochastic error term must be present in a regression equation?

Q: How do you determine whether a regression model is showing a case of redundancy?

A: Multicollinearity is simply redundancy in the information contained in predictor variables. If the…

Q: How can we say the Probit and logit regression models are nonlinear regression models used when Y is…

A: The logit model uses something known as the logistic distribution cumulative function. The probit…

Q: What problems might we encounter when using regression to measure causal effects?

A: Given: Regression is the Statistical method of detecting  exact relationship between dependent…

Q: What are the assumptions of the Regression analysis?

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Q: Explain the Two stage Least Square estimator in the general IV regression model?

A: Regression analysis of twostage minus squares (2SLS) is a statistical technique used in the analysis…

Q: What is the regression equation

A: The regression analysis is conducted here by using EXCEL. The software procedure is given below:…

Q: What is the logistic regression equation?   How would you interpret an odds ratio for a continuous…

A: The logistic regression is use to model the probability of events where who has two possibilities…

Q: The residuals from a linear regression model can be used to check the underlying assumptions and to…

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Q: If the correlation of the X's is equal to 1 or -1, then the regression cannot process. Why?

A: Correlation of X's means that the independent variables (IVs) are dependent on each other and this…

Q: What is the coefficient of determination and what is its significance? How prediction can be done…

A: The coefficient of determination (r2) defines the percent of variation of the response variable…

Q: What does the exponent of the regression coefficient represent in a logistic regression model?

A: what does the exponent of the regression coefficients represent in a logistic regression model?

Q: What is the connection between cointegration and spurious regression?

A: In general, regression models for non- stationary variables give spurious results .only  exception…

Q: What is the justification for using bayesian binary logistic regression model in a research?

A: Solution: Generally linear regression is used when the dependent variable is quantitative which is…

Q: Explain various Assumptions of the Fixed Effects Regression ?

A: The fixed effect principle is that the independent variables are correlated with the…

Q: Why is the null hypothesis for regression usually B 0?

A: The null hypothesis for regression usually β=0

Q: 3. Make a data analysis model using REGRESSION consisting of simple regression and multiple…

A: Given information: PRICE # BED # BATH SQ. FOOT 349,000 3 1 1240 165,000 4 2 2619 369,900 3…

Q: "In regression, the sum of squared error used for generating a regression line is"

A: Regression is used to find the relationship between one dependent variable and one or more…

Q: If the error term in a linear regression model is normally distributed, then the distribution of the…

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Q: 8) What are the assumptions of a simple linear regression model.

A: The assumptions of linear regression are as follows: 1) There should be linear relationship between…

Q: Explain Multivariate regression coefficients?

A: Independent and dependent variables in regression: In a simple regression, the variable of interest,…

Q: If all actual values of the dependent variable lie on the estimated regression line, then the…

A: From the given information, All the actual values of dependent variable are lie on the straight…

Q: Why is regression analysis the 'magic elixir'?

A: Regression analysics is a set of statistical methods used for the estimation of relationships…

Q: What is a numerical prediction from the regression line equation shown in the photo?

A: Here, the regression line equation is " Height ( in. ) = 52.293743 + 1.3679745 Shoe size ( in. ) ".…

Q: State true or false When a correlation coefficient for a linear regression model is close to -1 ,…

A: Given : Statement : When a correlation coefficient (corr. coeff.) for a linear regression(reg.)…

Q: What is regression models?

A: To define Regression model:

Q: What are the assumptions of the classical regression model(CRM)?

A: Assumption 1: Linear Parameter and correct model specification Assumption 1 requires that the…

Q: What is the interpretation of the slope beta1=-0.5 for the simple logistic regression with a…

A: The simple logistic regression model is a predictive algorithm using independent variables…

Q: Describe about the need of mathematical solution for least square regression line?

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Q: Write down the formula of least square regression line?

A: Let a be the intercept and b be the slope.

Q: What are the Assumptions of Extended Least Squares in the Multiple Regression Model?

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Q: State in algebraic notation and explain the assumption about the classical linear regression models…

A: Assumption of simple linear regression model

Q: 1. Develop a simple linear regression equation for starting salaries using an independent variable…

A: The simple linear regression equation is given by  y^=β0+β1x+∈i let X be a independent variables Let…

Q: Is the regression equation for predicting Y in terms of X the same as the regression line for…

A: Here we have to define  Is the regression equation for predicting Y in terms of X the same as the…

Q: What is the prediction interval equation for multiple linear regression when given σ ?

A: Prediction interval for multiple linear regression is given by Prediction interval

Q: When would a difference in difference regression model be an appropriate regression model to…

A: let us first try to understand the basis of regression analysis Definition: Regression analysis is a…

Q: What is the standard error of estimate?

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Q: If the Pearson correlation between X and Y is negative, then the regression equation will have a…

A: Conditions based on sign with respect to the correlation coefficient and slope:   As the…

Q: What is meant by the Regression equation?

A: A regression equation is a statistical model that show the relationship between the predictor…

Q: State the null hypothesis in testing the significance of the overall multiple regression equation.…

A: Answer- For the overall multiple regression equation, hypothesis is- Null Hypothesis, H0: The…

Q: Define Regression Methods?

A: Introduction The regression equation is used for the prediction of y values which depends upon the…

Q: What are the different ways to reduce the error in least square regression?

A: The error term follows normal distribution with mean 0 and constant variance. The error term is same…

Q: Define Residuals or errors in Alternative Regression Models?

A: The residual or errors is defined as the difference between the observed value of the dependent…

Q: Why is the null hypothesis for regression usually B- 0?

A: Regression analysis: The regression analyzes the relationship between the predictor or independent…

Q: What do you mean by Generalized method of moments? illustrate regression model with exogenous…

A: The generalized method of moments is a method of estimation that provides an accurate and quick…

Q: Does correcting the sugar cane model for heteroscedasticity improve its performance? Interpret the…

A: R-squared is called regression coefficient, In first picture it is 0.48694 The sign of a regression…

Q: What is the estimate of the parameter o in the regression model?

A: Given that The regression equation is y = -3.05 + 0.10x MS(error) = 1.40

Q: IS the following statment true or false, please explain why    For each x term in the multiple…

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Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related. 

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.