Your lab partner decides to incorrectly compute the estimate of the slope parameter for the least-squares line as follows: see picture. The problem with such a computation is that: a) it will maximize squared error instead of minimize it b) it will likely not provide a good estimate for the intercept of the equation c) it will not result in the slope for the least-squares line d) it will be undefined since the denominator will equal 0 e) none of the above
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.
Your lab partner decides to incorrectly compute the estimate of the slope parameter for the least-squares line as follows: see picture.
The problem with such a computation is that:
a) it will maximize squared error instead of minimize it
b) it will likely not provide a good estimate for the intercept of the equation
c) it will not result in the slope for the least-squares line
d) it will be undefined since the denominator will equal 0
e) none of the above
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