Answer true or false to each of the following statements and explain your answers.a. Statistical methods designed for a particular set of assumptions may not perform well if the assumptions are violated.b. The presence of outliers in the values of the response variable can result in decreased values of the t-statistics for the utility of individual predictor variables.c. Generally, a regression model will predict as well or better for a new set of data than for the data from which it was developed.
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.
Answer true or false to each of the following statements and explain your answers.
a. Statistical methods designed for a particular set of assumptions may not perform well if the assumptions are violated.
b. The presence of outliers in the values of the response variable can result in decreased values of the t-statistics for the utility of individual predictor variables.
c. Generally, a regression model will predict as well or better for a new set of data than for the data from which it was developed.
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