Calibri B 11 A B D FW3 E FW4 F G Barefoot FW1 w2 34.851 32.927 2 37.455 31.719 27.937 27.483 20.687 32.626 21.336 28.229 21.749 30.889 37.565 14.573 17.309 30.921 18.468 11.617 23.863 26.681 3 32.616 23.067 28.614 26.665 26.056 24.865 28.931 4 31.59 37.228 27.908 23.782 23.766 25.293 5 24.749 24.809 31.218 23.64 37.264 27.016 27.615 29.044 27.416 30.716 22.181 27.281 31.016 20.052 17.486 11.296 20.186 6 30.978 22.463 25.386 7 9 10 18.079 20.909 19.659 32.875 12.859 16.772 16.289 23.155 24.625 18.363 21.66 21.808 27.784 20.623 21.233 21.54 30.725 11 17.609 20.369 28.188 28.678 29.013 22.501 29.013 12.07 14.428 24.308 24.325 31.178 22.121 25.89327.762 25.498 20.586 27.119 26.509 12 13 14 15 16 17 31.301 25.894 19.964 23.087 25.475 24.97 30.305 27.35 20.387 26.953 33.153 23.463 33.45 33.77 28.263 24.015 18 21.203 25.033 23.86 22.761 26.053 29.894 23.954 20.402 23.434 20.321 20.325 21.877 20.653 26.294 26.093 17 I6డి ఎ3.874 7 రీతర) 19 26.065 34.133 16.658 27.805 30.123 28.414 20 15.032 26.853 27.778 27.457 26.625 27.539 15.2 33.395 19.357 21 22 15.447 22.073 23.924 25.478 13.807 24,112 16.114 22.7 డ0.700 20.334 23 24 25 16.365 29.161 30. 178 25.869 31.884 12.127 26 27 22.533 23.005 18.487 19.14 ட9.155 21.793 20111 1214) 29 Sheet i
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.
In particular, note the variables Barefoot and Footwear1. Barefoot represents a subject's range of ankle motion (in degrees) while barefoot, and Footwear1 represents their range of ankle motion (in degrees) while wearing typical shoes.
Use this data and your preferred software to calculate the equation of the least-squares linear regression line to predict a subject's range of ankle motion while wearing typical shoes, y^ , based on their range of ankle motion while barefoot, x . Round your coefficients to two decimal places of precision.
In order to assess the linear regression equation's ability to predict range of ankle motion, the physical therapist reviewed a
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