(c) Is the multiple regression model useful for predicting catch time? Test the relevant hypotheses using a = 0.05.State the null and alternative hypotheses.O Ho: at least one of ₁ or ₂ is not 0.H₂ B₁ B₂=ⒸH₁: B₁ = B₂ = 0= = 0H₂: at least one of ₁ or ₂ is not 0.Ho: B₁ = B₂ = 0H₂: neither B₁ nor B₂ is 0.O Ho: neither B₁ nor B₂ is 0.H₂: B₁ = B₂ = 0Calculate the test statistic. (Round your answer to two decimal places.)F =Use technology to calculate the P-value. (Round your answer to four decimal places.)P-value =What can you conclude?Reject Ho. We have convincing evidence that the multiple regression model is useful and can conclude that neither B₁nor● Reject Ho. We have convincing evidence that the multiple regression model is useful and can conclude that at least one of ₁ or ₂ isnot 0.O Fail to reject Ho. We do not have convincing evidence that the multiple regression model is useful and cannot conclude that ₁ andB₂ are both not 0.ŷO Fail to reject Ho. We do not have convincing evidence that the multiple regression model is useful and cannot conclude that at leastone of B₁ or B₂ is not 0.(d) The authors of the article suggest that a simple linear regression model with the single predictorlengthspeedB₂ is 0.X =might be a better model for predicting catch time. Calculate these x values and use them to fit a simple linear regression model. (Round yournumerical values to three decimal places.) A statistical program is recommended.The authors of an article found that the speed of a prey (twips/s) and the length of a prey (twips x 100) are good predictors of the time (seconds)required to catch the prey. (A twip is a measure of distance used by programmers.) Data were collected in an experiment in which subjects wereasked to "catch" an animal of prey moving across his or her computer screen by clicking on it with the mouse. The investigators varied the length ofthe prey and the speed with which the prey moved across the screen.The following data are consistent with summary values and a graph given in the article. Each value represents the average catch time over allsubjects. The order of the various speed-length combinations was randomized for each subject.Prey Length Prey Speed Catch Time76543346776576753632020S2020204040404080608010010012080801001201.091.211.241.401.501.411.361.291.281.391.371.411.441.431.711.501.401.501.89(a) Fit a multiple regression model for predicting catch time using prey length and speed as predictors. (Use x₁ for prey length and x₂ for speed.Round your numerical values to three decimal places.)ŷ(b) Predict the catch time for an animal of prey whose length is 6 and whose speed is 50. (Round your answer to three decimal places.)

Question

(c) Is the multiple regression model useful for predicting catch time? Test the relevant hypotheses using a = 0.05.State the null and alternative hypotheses.O Ho: at least one of ₁ or ₂ is not 0.H₂ B₁ B₂=ⒸH₁: B₁ = B₂ = 0= = 0H₂: at least one of ₁ or ₂ is not 0.Ho: B₁ = B₂ = 0H₂: neither B₁ nor B₂ is 0.O Ho: neither B₁ nor B₂ is 0.H₂: B₁ = B₂ = 0Calculate the test statistic. (Round your answer to two decimal places.)F =Use technology to calculate the P-value. (Round your answer to four decimal places.)P-value =What can you conclude?Reject Ho. We have convincing evidence that the multiple regression model is useful and can conclude that neither B₁nor● Reject Ho. We have convincing evidence that the multiple regression model is useful and can conclude that at least one of ₁ or ₂ isnot 0.O Fail to reject Ho. We do not have convincing evidence that the multiple regression model is useful and cannot conclude that ₁ andB₂ are both not 0.ŷO Fail to reject Ho. We do not have convincing evidence that the multiple regression model is useful and cannot conclude that at leastone of B₁ or B₂ is not 0.(d) The authors of the article suggest that a simple linear regression model with the single predictorlengthspeedB₂ is 0.X =might be a better model for predicting catch time. Calculate these x values and use them to fit a simple linear regression model. (Round yournumerical values to three decimal places.) A statistical program is recommended.The authors of an article found that the speed of a prey (twips/s) and the length of a prey (twips x 100) are good predictors of the time (seconds)required to catch the prey. (A twip is a measure of distance used by programmers.) Data were collected in an experiment in which subjects wereasked to &#34;catch&#34; an animal of prey moving across his or her computer screen by clicking on it with the mouse. The investigators varied the length ofthe prey and the speed with which the prey moved across the screen.The following data are consistent with summary values and a graph given in the article. Each value represents the average catch time over allsubjects. The order of the various speed-length combinations was randomized for each subject.Prey Length Prey Speed Catch Time76543346776576753632020S2020204040404080608010010012080801001201.091.211.241.401.501.411.361.291.281.391.371.411.441.431.711.501.401.501.89(a) Fit a multiple regression model for predicting catch time using prey length and speed as predictors. (Use x₁ for prey length and x₂ for speed.Round your numerical values to three decimal places.)ŷ(b) Predict the catch time for an animal of prey whose length is 6 and whose speed is 50. (Round your answer to three decimal places.)

Accepted Answer

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