Unit Vii Essay Correlation Of Data Points. Management Essay

Unit VII Essay
Correlation of Data Points
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In an essay of no less than three pages, explain the correlation of the data points to the equations shown in Figure 4.3 on page 119 (How can better data be acquired?), andreview Figures 4.4A, 4.4B, and 4.4C on page 120. What assumptions are being shown in these figures?
Linear regression is a statistical technique aimed at analyzing the relationship between one or more independent value (X) and a dependent value (Y). The independent variable (cause) explains a dependent variable and is useful to predict the values of a variable and approximate. In regression models one can assess correlation, which measures the strength of the linear (or straight-line) relationship between two variables. Plotting the variables in a scattergram or scatter plot is one to assess the strength of the linear relationship. To plot the correlation between these two variables on a scatter plot graph, on the axis of x (horizontal) as the independent variable, while on the y (vertical) axis is the dependent variable. In the equation Ŷ = 2 + 1.25X, the coefficient of determination (r2) is 0.6944 and the coefficient of correlation is 0.83 (Render et al., 2018). Since the correlation of coefficient is ​​close to 1, the correlation is strong and direct, and it gets stronger as it gets closer.
Correlation may show that the variables are causally related, but correlation does not imply causation. There is a positive correlation (0
The normality assumption is also considered in correlation since regression is a linear analysis and works with linear relationships. When variable errors have non normal distribution, they can affect relationships and significance, and focus on mistakes because in a linear regression. The the error patterns can help indicate whether the relationship is linear or random. Other commonly used statistical procedures assume the normality of the observed data. Theoretical justification for the use of statistical evidence involving normal distributions is based on the normality assumption when the estimators of the linear function of variables are normally distributed.
There is an assumption that it is possible to assess the strength of the relationship. In a perfect linear relationship when X changes by one point, Y also changes by the same value. However, in reality the relati...