If a regression analysis was to be completed on body mass index (BMI), what could be an independent variable in that analysis? Why? If we could, what other independent variables should be included in the analysis? What statistic(s) would show the value of that regression in understanding BMI?

Q: What is the causal effect of gun control on life expectancy? b. What potential sources of bias…

A: There are two different conditions - one with gun control law and another without gun control law.…

Q: How can we use Eviews to tell if a regression suffers from first order autocorrelation and what are…

A: First-order autocorrelation: First-order autocorrelation is a type of serial correlation or…

Q: Discuss the advantages and disadvantages of using data from an observational study to perform a…

A:

Q: What is a line of best fit (aka. trend line, regression line, Linear regression model)? Why would we…

A: We need to answer about a line of best fit and why we want one.

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: Which assumptions is not required for unbiasedness of regression parameters?

A: As options are not given here but we know that there are 4 assumptions for unbiasedness of…

Q: What is the role of error term , ?? in regression analysis? What is the  difference

A: *Answer :

Q: Discuss the importance of testing for serial correlation, multicollinearity and the significance of…

A: Serial correlation is used to explain the relationship among observed of the same variable over…

Q: Explain assessing the validity of a regression model for forecasting?

A: Predictions for regression are true only for the data set used to estimate the model. The…

Q: What is regression? why are there in general two regression lines? under what conditions properties…

A: Regression is a statistical method used in finance, investing, and otherdisciplines which attempts…

Q: Define Internal and External Validity When the Regression Is Used for Forecasting?

A: A statistical analysis has internal validity when the statistical inference regarding causal effects…

Q: What is difference between chi and binomial statistics?  When do we use regression analysis?

A: Hey there.! thank you for posting your question hope you're doing well.

Q: Why is it often preferable to use more than one predictor variable in a regression analysis?

A: In a regression analysis, the presence of more number of predictor variables means that more number…

Q: Describe the potential effects of outliers on performing statistical inference regarding the utility…

A: Effects of outliers in data:

Q: What two plots did we use in this chapter to decide whether we can reasonably presume that the…

A:

Q: The attached results are for a multiple regression study of smartphone addiction (SSA-SV) proneness…

A: The study was based on smartphone addiction (SSA-SV) proneness in relation to 1) Gender 2)Age 3)…

Q: Explain various Assumptions of the Fixed Effects Regression ?

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

Q: What are the possible consequences of the presence of outliers in the data used for conducting a…

A: An outlier is an observation that is distant from the other values in a data set. It causes serious…

Q: How is the number of degrees of freedom available for estimating , the variance of ε, related to the…

A: Let n be total number of variables       k be number of independent variables

Q: Explain Multivariate regression coefficients?

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

Q: Using data from the 2008 General Social Survey (GSS), political psychologists were interested in…

A: Regression model: For the sake of convenience, we denote the response variable, the number of…

Q: Do you think the regression in Table 5 suffers from omitted variable bias? If yes, which additional…

A: Regression is used to predict the value of dependent variable based on one or more independent…

Q: Define errors of prediction in a scatter plot with a regression line?

A:

Q: approach is not used to analyzing the quality of the estimated regression lin

A: ANOVA is regression is used to to test the relationship between the variables under consideration.…

Q: How the most common use of a one-sided t-test is to determine whether a regression coefficient ?

A:

Q: A process by which we estimate the value of dependent variable on the basis of one or more…

A: Regression is the process in which we find the value of a dependent variable on the basis of one or…

Q: If the coefficient of determination is 0.298, what percentage of the data about the regression line…

A: Coefficient of determination It tells us the percentage of variation  in the dependent variable that…

Q: Explain the IV Regression Assumptions?

A: Introduction: A multiple regression analysis is often found to contain endogenous predictor…

Q: What is the odds ratio for a study with a logistic regression coefficient -0.25254?

A: Odd ratio using logistic regression coefficient is given by Odd ratio= e(logistic regression…

Q: Question 16: Confidence interval for a simple linear regression coefficient Bis:

A:

Q: What is a simple way to check for normality of residuals in a regression model?

A: First of all, testing of normality of residual is important for any regression model because it it…

Q: Define "regression coefficient"?

A:

Q: Explain how the variance inflation factor (VIF) affects the estimated standard deviation of a…

A: Variance inflation factor:Variance inflation factor of a variable is the ratio of the variance of…

Q: Define concept of IV Regression with Heterogeneous Causal Effects?

A: The simple IV regression model is easily extended to a multiple regression model which is called the…

Q: in multiple regression analysis, a residual is the difference between the value of a dependent…

A: We know that, In any regression model, Residual is the difference between the value of a dependent…

Q: describe how each characteristic is related to BMI. Are crude and multivariable effects similar?…

A: Every variable with less than 0.05 p-value is associated with BMI. So, Age, Total Serum Cholestrol…

Q: Discuss the advantages of using data collected from a designed experiment in performing a regression…

A: In a designed experiment the experimenter collects the data according to their requirements.

Q: If the regression line is not a "good fit" what would be better to use to approximate a response…

A: Mean is a measure of central tendency of a set of observations.

Q: Based on the above regression results does jailing more criminals ((INPRISON06) reduce violent crime…

A: Given data: Summary outputs and ANOVA results for multiple linear regression are provided. Here, the…

Q: A colleague of yours is completing a final report on the causes of the frequency of cyberbullying.…

A: We can use t and F statistic to conduct the significance test of OLS regression model.

Q: Do you think the regression results have been affected by the multicollinearity issue? Why or why…

A: What is multicollinearity Multicollinearity is problem where one or more than one independent…

Q: A logistic regression was used to investigate obesity and poor physical health while controlling for…

A: Logistic regression is used when the dependent variable is categorical and the independent variables…

Q: Explain the concept of OLS Estimators, Predicted Values, and Residuals in the Multiple Regression…

A: In a linear regression model, ordinary least squares (OLS) is a type of linear least squares method…

Q: Explain the concept of Asymptotic Distribution of the OLS Estimatorand t-Statistic in the multi…

A: OLS is the Ordinary least square . Which is the most common estimation method for linear models and…

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: You are analyzing a dataset containing 379 datapoints, and want to use 13 predictor variables to…

A: A multiple linear regression model is considered.

Q: What are the different measures used for the OLS estimate of the multiple regression line?

A: Multiple linear regression (MLR) is used among a number of random variables to determine the…

Q: Explain why all-subsets regression is considered superior to stepwise regression in selecting a…

A: All-subsets regression: The all-subsets regression considers all the predictors available to predict…

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.