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# Tools hree other groups that used the same metal salt- age Mass of met.docx

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# Tools hree other groups that used the same metal salt- age Mass of met.docx

Tools hree other groups that used the same metal salt. age Mass of metal Salt(g) Mass of Product(g) Your Data Group 2 Group 3 Group 4 0.30 0.40 0.50 0.60 0.66 0.38 0.64 0.72 Graph mass of product vs mass of metal salt 3. Linear regression equation y 0.44x+ 0.402 4. R2 value R- 0.14235 5. Is there are linear correlation between mass of product and mass of salt used? Explain, in detailed. Currently editing an Entry
Solution
The correlation between mass of product and mass of salt used is not linear. This is determined from the value of R 2 which is very low. R 2 value is a measure of how well the given data fits the predicted model where predicted model in this case is the line of regression whose equation is y = 0.44x + 0.402. If the R 2 value is 0 (zero) then none of the data fits the predicted model and if the R 2 value is 1 then all the data fits the predicted model and future or intermediate data points can be calculated using the model equations. Here the R 2 is 0.14235 which is close to zero, indicating that the given data of mass of product and mass of salt used does not fit well into the predicted model of straight line (linear relationship) and the correlation is not linear.
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Tools hree other groups that used the same metal salt. age Mass of metal Salt(g) Mass of Product(g) Your Data Group 2 Group 3 Group 4 0.30 0.40 0.50 0.60 0.66 0.38 0.64 0.72 Graph mass of product vs mass of metal salt 3. Linear regression equation y 0.44x+ 0.402 4. R2 value R- 0.14235 5. Is there are linear correlation between mass of product and mass of salt used? Explain, in detailed. Currently editing an Entry
Solution
The correlation between mass of product and mass of salt used is not linear. This is determined from the value of R 2 which is very low. R 2 value is a measure of how well the given data fits the predicted model where predicted model in this case is the line of regression whose equation is y = 0.44x + 0.402. If the R 2 value is 0 (zero) then none of the data fits the predicted model and if the R 2 value is 1 then all the data fits the predicted model and future or intermediate data points can be calculated using the model equations. Here the R 2 is 0.14235 which is close to zero, indicating that the given data of mass of product and mass of salt used does not fit well into the predicted model of straight line (linear relationship) and the correlation is not linear.
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### Tools hree other groups that used the same metal salt- age Mass of met.docx

1. 1. Tools hree other groups that used the same metal salt. age Mass of metal Salt(g) Mass of Product(g) Your Data Group 2 Group 3 Group 4 0.30 0.40 0.50 0.60 0.66 0.38 0.64 0.72 Graph mass of product vs mass of metal salt 3. Linear regression equation y 0.44x+ 0.402 4. R2 value R- 0.14235 5. Is there are linear correlation between mass of product and mass of salt used? Explain, in detailed. Currently editing an Entry Solution The correlation between mass of product and mass of salt used is not linear. This is determined from the value of R 2 which is very low. R 2 value is a measure of how well the given data fits the predicted model where predicted model in this case is the line of regression whose equation is y = 0.44x + 0.402. If the R 2 value is 0 (zero) then none of the data fits the predicted model and if the R 2 value is 1 then all the data fits the predicted model and future or intermediate data points can be calculated using the model equations. Here the R 2 is 0.14235 which is close to zero, indicating that the given data of mass of product and mass of salt used does not fit well into the predicted model of straight line (linear relationship) and the correlation is not linear.