Two specimens of cold rolled steel sheet, which have different copper contents and annealing temperature are measured in hardness with the following results: First column = Hardness Second column = Copper content Third column = Annealing temperature a) Create a scatter pl
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.
Two specimens of cold rolled steel sheet, which have different
copper contents and annealing temperature are measured in hardness with the following results:
First column = Hardness
Second column = Copper content
Third column = Annealing temperature
a) Create a scatter plot to verify that it is reasonable to assume that the regression of Y on x is linear.
b) Fit a straight line using the method of least squares.
c) Fit an equation of the form (image 2), where x1 represents the copper content, x2 represents the annealing temperature, and y represents the hardness.
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Solved in 3 steps with 2 images
