1) Sara believes that as she increases her walking speed, her pulse rate will increase. Sara records her pulse rate, in beats per minute (bpm), while walking at each of seven different speeds, in miles per hour (mph). Regression Analysis: Palse Versus Speed Predictor Constant Speed Coef 63.457 16.2809 SE Coef 2.387 0.8192 26.58 19.88 0.000 0.000 S-3.087 R-Sq = 98.7% R-Sa (adi) = 98.5% a) Is there evidence at the 1% level to show a positive linear relationship between walking speed and pulse rate? Assume conditions for inference are satisfied. b) Interpret the p-value in context. c) Construct an interval to support the conclusion to part a. Make sure to briefly explain how it supports the conclusion. d) Interpret the interval.
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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