How to Check the non-constant variance using this ’residuals vs fitted values’ plot?

Q: A company that manufactures computer chips wants to use a multiple regression model to study the…

A: Given : Analysis of variance (ANOVA) table Source of variation  Degrees of freedom Sum of squares…

Q: Discuss how to choose the appropriate benchmark for performance evaluation USING REGRESSION R…

A: Using Regression R Squared

Q: Explain role of the instrument relevance condition in IV regression?

A: An instrumental variable (sometimes referred to as a "instrument" variable) is a third variable…

Q: How are the distribution of the observed residuals of the constructed model tested for normality?…

A: A normality plot (Q-Q plot) can be made along with the regression line for the obtained predicted…

Q: A study was performed on 64 female college athletes. Researchers collected data on each female…

A:

Q: 0.10 v_i 0.20 0.30 0.00 0 50 80000 100 ශ්‍රසි Leverage values о 150 200

A: The provided chart of regression model analysis:The reason for using this type of plot in analyzing…

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

A: *Answer :

Q: shown below is a portion of a computer output for a regression analysis relating supply (y in…

A: Comment: As per the our company guidelines we are supposed to answer only three subparts. Kindly…

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: Aggregate data were collected for a recent year in 44 Denver neighborhoods on various demographic…

A: The partial ANOVA table is given.

Q: You want to look at an ANOVA table of a regression in which a dependent variable is predicted using…

A: The total number of observations is n = 7 and the F-ratio is, 15. The residual sum of squares is RSS…

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

A: Effects of outliers in data:

Q: What is the expected average height of 8 year old boys, using the regression equation?

A: From the given information, the obtained regression equation is y=27.84+2.573x.

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: Investigators want to assess the association between initial serum cholesterol levels (mg/100ml) and…

A: Here, there are serum cholesterol and coronary artery given and we will check association between…

Q: How do we test whether a regression is significant? Please be as specific as possible. Be sure to…

A: The regression is significant.

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

A:

Q: Linear Regression models can be optimised to avoid high variance by means of regularisations such as…

A: If the linear model contains many predictor variables or if these variables are correlated, the…

Q: How to use simple linear regression model to find 90% confidence interval for the mean of y,…

A: Given, Confidence level = 90% for simple linear regression model of Y on X.

Q: Define and explain regression and coorelation in statistics seperately with advantages and…

A: Regression Analysis: Regression analysis is used to study the relationship between two or more…

Q: You have these 3 histograms:  Histogram of Residuals: X-axis: Residual values (deviation between…

A: Student's t-distribution: When a sample of size 'n' is selected from normal distribution, the…

Q: Describe the difference between a residual and a standardized residual. Which of these two residuals…

A: Difference between residual and standardized residual is shown below

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: fit to a data set with p predictor variables, and the adjusted R-squared value is 0.75. What can we…

A: Multiple regression model y = b0+b1x1+b2x2 Independent variables x1 and x2 Dependent variable y…

Q: Based on the regression output, what is the predicted number of wins for a team with a payroll of…

A: It is given that The regression equation is Wins = 67.6 + 0.215 Payroll

Q: What is a “residuals plot” and how is it used in assessing linearity of calibration curves?

A: Residual plot is the graphical representation of the residuals of the regression model.

Q: What kind of plot is useful for deciding whether it is reasonable to find a regression plane for a…

A: Scatterplot matrix:A scatterplot matrix is an array or a collection of scatterplots, consisting of…

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: ) Hence test whether ? is significant. Give reasons for your answer.

A: From the above output  The test statistic F=7954393/925892 F=5.31  P value of the test statistic is…

Q: The concentration of dissolved solids and the turbidity of stream are measured simultaneously for…

A: Given: Do mg|L Turbidity 400 5 550 30 700 32 800 58 500 20

Q: (a) What does the scatterplot suggest about the relationship between depression score change and BMI…

A: a) From the scatter plot, it is clear that there exists a linear relationship between X and Y.…

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.