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Tiple covariance Szy Sample formula ¸Σ₁=₁(x¡—x)*(Yi−y) n-1 Sxy=

Tiple covariance Szy Sample formula ¸Σ₁=₁(x¡—x)*(Yi−y) n-1 Sxy=

Algebra & Trigonometry with Analytic Geometry
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter10: Sequences, Series, And Probability
Section10.8: Probability
Problem 31E
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Given are data on = age and y = number of days after arthroscopic shoulder surgery before being able to return to sport for 10 weight lifters: I 33 31 32 28 33 26 34 32 28 27 y 6 4 4 1 3 3 4 2 3 2 1. Construct a scatterplot, and comment on any interesting features observed. To plot, use your knowledge in plotting points in the Cartesian plane (rectangular coordinate system) but this time limit your axes to positive x-axis and positive y-axis. 2. Is there a linear association between age and days? Explain using the scatterplot or refer to the sample illustration below. Example of positive Example of negative Example of no comelation correlation correlation Example of strong positive correlation Example of weak negative correlation
Transcribed Image Text:Given are data on = age and y = number of days after arthroscopic shoulder surgery before being able to return to sport for 10 weight lifters: I 33 31 32 28 33 26 34 32 28 27 y 6 4 4 1 3 3 4 2 3 2 1. Construct a scatterplot, and comment on any interesting features observed. To plot, use your knowledge in plotting points in the Cartesian plane (rectangular coordinate system) but this time limit your axes to positive x-axis and positive y-axis. 2. Is there a linear association between age and days? Explain using the scatterplot or refer to the sample illustration below. Example of positive Example of negative Example of no comelation correlation correlation Example of strong positive correlation Example of weak negative correlation
3. Compute the sample covariance szy Sample formula Σ₁(xi-x)*(yi-y) Sxy= n-1 4. Compute ther and interpret it using the interpretation table below: Interpreting Pearson's r <0.2 = very weak relationship = weak relationship 0.2-0.4 0.4-0.6 = moderate relationship = strong relationship 0.6-0.8 > 0.8 = very strong relationship
Transcribed Image Text:3. Compute the sample covariance szy Sample formula Σ₁(xi-x)*(yi-y) Sxy= n-1 4. Compute ther and interpret it using the interpretation table below: Interpreting Pearson's r <0.2 = very weak relationship = weak relationship 0.2-0.4 0.4-0.6 = moderate relationship = strong relationship 0.6-0.8 > 0.8 = very strong relationship
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4. Compute ther and interpret it using the interpretation table below: Interpreting Pearson's r < 0.2 = very weak relationship = weak relationship 0.2-0.4 0.4-0.6 0.6-0.8 >0.8 = moderate relationship = strong relationship = very strong relationship
Transcribed Image Text:4. Compute ther and interpret it using the interpretation table below: Interpreting Pearson's r < 0.2 = very weak relationship = weak relationship 0.2-0.4 0.4-0.6 0.6-0.8 >0.8 = moderate relationship = strong relationship = very strong relationship
2. Is there a linear association between age and days? Explain using the scatterplot or refer to the sample illustration below. Example of positive Example of negative Example of no correlation correlation correlation X Example of strong positive correlation Example of weak negative correlation
Transcribed Image Text:2. Is there a linear association between age and days? Explain using the scatterplot or refer to the sample illustration below. Example of positive Example of negative Example of no correlation correlation correlation X Example of strong positive correlation Example of weak negative correlation
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