i believe iheet the date hea ne and CTinical Studies UMI pre-pregnaney tx, in k
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i believe iheet the date hea ne and CTinical Studies UMI pre-pregnaney tx, in k myot born weigs yingras nady swgrests The lIMI pre-pregnancy (, in ow hard he ody and us a duce the uct a scalter plot for these data esd the estimated regression line e. Estimsate the e e Eornancy BMI is 25 kam ected weight of a newborn if the mothers 12.32 Public He s not available, do you helieve that BMl is every county in s Meal Cap 2013 d. If ultrasound nota uof birth weight? Why or why nort , physicaunt for large cargo ships. One method or predic- cach. miuu pt the wind speed (x, in knots) is linearly relatedConsr and the food in sciences Deep-water 300 m) wave foresdults and chitle -uigests tra (y, in feet). A random sample ofbuoys was e egd sneed and wave height was measured at and and the wind The data are given in the following table 12 ALKING huained, aata are given in the following table! WAVES b. Find th Nind speed9 11 10 10 hight 2.9 14 1.7 09 1.2 LO 1 958 589129 129 Wind speed 2.6 3.0 1.7 2.1 15 Challen ht 1.9 0.1 Wave heig Wind speed 12 8 a. Find the estimated iegsession line 12.33 Me the choles height 3.1 2.7 4 2.5 1.7 0.6 0.7 1.4 as a meas di between c. Find the coefficient of determination. Interpret this value. d. Suppose a 10-foot wave is considered to be the storm threshold. What wind speed yields an expected storm b. Complete the ANOVi table (without the p value) threshold? 1231 Manufacturing and Product Development There is good evidence to suggest that the depth of a bounce on a certain eicular trampoline is linearly related to the stiffhessof theExplanation / Answer
Soolution
data for regression model.
Kindly check if entered vakues are correct..
Image was bit blurred
Regrression output form excel is
The estimated regression line is
wind height=-0.8107+0.268296(wind speed)
y intercept=-0.8107
slope=0.268296
Solutionb:
Solutionc:
coefficient of determination =R sq
R sq=0.4046
0.4046*100=40.46% variation in wind height is explained by wind speed.
Solutiond:
wind height is given
=10 foot
substitute in regression eq
wind height=-0.8107+0.268296(wind speed)
10=-0.8107+0.268296(wind speed)
windspeed=10+0.8107/0.268296
windspeed=40.29
windspeed =40(rounding to nearest integer as given in data)
windspeed waveheight 9 2.9 11 1.4 10 1.7 10 0.9 11 1.2 9 1 9 1.5 6 0.7 9 1.9 5 0.1 8 2 9 2.6 12 3 9 1.7 12 2.1 9 1.5 12 3.1 8 2.7 7 0.4 13 2.5 9 1.7 8 0.6 6 0.7 8 1.4Related Questions
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