Aortic stenosis refers to a narrowing of the aortic valvein the heart. The article “Correlation Analysis ofStenotic Aortic Valve Flow Patterns Using PhaseContrast MRI” (Annals of Biomed. Engr., 2005:878–887) gave the following data on aortic root diameter(cm) and gender for a sample of patients having variousdegrees of aortic stenosis:M: 3.7 3.4 3.7 4.0 3.9 3.8 3.4 3.6 3.1 4.0 3.4 3.8 3.5F: 3.8 2.6 3.2 3.0 4.3 3.5 3.1 3.1 3.2 3.0a. Compare and contrast the diameter observations forthe two genders.b. Calculate a 10% trimmed mean for each of the twosamples, and compare to other measures of center(for the male sample, the interpolation method mentionedin Section 1.3 must be used).
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.
Aortic stenosis refers to a narrowing of the aortic valve
in the heart. The article “
Stenotic Aortic Valve Flow Patterns Using Phase
Contrast MRI” (Annals of Biomed. Engr., 2005:
878–887) gave the following data on aortic root diameter
(cm) and gender for a sample of patients having various
degrees of aortic stenosis:
M: 3.7 3.4 3.7 4.0 3.9 3.8 3.4 3.6 3.1 4.0 3.4 3.8 3.5
F: 3.8 2.6 3.2 3.0 4.3 3.5 3.1 3.1 3.2 3.0
a. Compare and contrast the diameter observations for
the two genders.
b. Calculate a 10% trimmed mean for each of the two
samples, and compare to other measures of center
(for the male sample, the interpolation method mentioned
in Section 1.3 must be used).
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