In particular, note the variables Barefoot and Footwear5. Barefoot represents a subject's range of ankle motion (in degrees) while barefoot, and Footwear5 represents their range of ankle motion (in degrees) while wearing compression hosiery and medical 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 compression hosiery and medical shoes, ?̂ , based on their range of ankle motion while barefoot, ? . Round your coefficients to two decimal places of precision.
In particular, note the variables Barefoot and Footwear5. Barefoot represents a subject's range of ankle motion...
A group of physics students collected data from a test of the projectile motion problem that was analyzed in a previous lab exercise (L5). In their test, the students varied the angle and initial velocity Vo at which the projectile was launched, and then measured the resulting time of flight (tright). Note that tright was the dependent variable, while and Vo were independent variables. The results are listed below. (degrees) Time of Flight (s) Initial Velocity V. (m/s) 15 20...
The Excel file: DASSxlsx contains information recorded on a sample of 40 of the college students' responses. The file contains the DASScore (representing level of mood) and the Arxiety Score for each student Download the data file and fit a linear regression model for predicting DASSScore (Y) from AnxietyScore (0) Use your Excel output, and any other information provided to answer the following questions. For each question, either choose the most correct option, or type in the answer to the...
Can you please answers these four questions as aoin as possible please and thank you! Given are five observations for two variables, z and y 5 13 20 18 48 57 11 27 a. Choose the corre rect scatter diagram for these data: A. B. 60+ 60 50 50 40 40 30+ 30 20 20 10 10- 10 20 30 40 50 60 x 10 20 30 40 50 60 57 x y 60 60 50+ 50- 40- 40+ 30-...
The following ANOVA model is for a multiple regression model with two independent variables: Degrees of Sum of Mean Source Freedom Squares Squares F Regression 2 60 Error 18 120 Total 20 180 Determine the Regression Mean Square (MSR): Determine the Mean Square Error (MSE): Compute the overall Fstat test statistic. Is the Fstat significant at the 0.05 level? A linear regression was run on auto sales relative to consumer income. The Regression Sum of Squares (SSR) was 360 and...