a. Rewrite the data points (3,1), (6,3), (7,6) and (9,6) with new x-coordinates in mean-deviation form. Let X be the associated design matrix. Why are the columns of X orthogonal? b. Write the normal equations for the data in part (a), and solve them to find the least-squares line, y = Bo + B,x*, where x* =x-6.25. a. The data in mean-deviation form are (Type ordered pairs. Use a comma to separate answers as needed.) The associated design matrix, X, is . Therefore, the columns of X are orthogonal because (Simplify your answer. Use ascending order.) b. Write the normal equations for the data from part (a). Select the correct choice below and fi (Simplify your answer.) the entries in one column are all 1 and the entries in the other column sum to 0. O A. Po Pi the entries in one column are all 1 and the entries in the other column sum to - 1. Bo В. one column contains all zeros. The least-squares line, y = Po +B,x , is y= (x-6.25).
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.
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