The data show systolic and diastolic blood pressure of a sample of people. x (Systolic) 149 141 122 114 132 141 135 140 y (Diastolic) 104 81 87 80 77 101 91 99 a. Find the value of the linear correlation coefficient: r = nothing (Round to three decimal places as needed.) b. Find the critical value for determining if there is a correlation between systolic and diastolic pressure in the population of all people. Critical value = nothing (Round to three decimal places as needed.) c. Is there a linear correlation between systolic and diastolic pressure in the population of all people. A. No B. Yes d. Find the regression equation that describes the diastolic pressure in terms of the systolic pressure. yequals nothingplusnothing x (Round to two decimal places as needed.) e. Find the best predicted diastolic pressure for a person with a systolic reading of 146 . yalmost equals nothing (Round to one decimal place as needed
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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x (Systolic)
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149
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y (Diastolic)
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104
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nothingplusnothing
nothing
(Round to one decimal place as needed.
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