Explain the method of fitting of an exponential curves of the form (i)Y = abX and (ii) Y = aebx to the given data.
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- The line of best fit through a set of data is ý = 14.714 – 3.985x According to this equation, what is the predicted value of the dependent variable when the independent variable has value 180? Round to 1 decimal place.A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-1.226 b=33.622 r²-0.4489 r=-0.67 Use this to predict the number of situps a person who watches 3 hours of TV can do (to one decimal place)A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: ý = bo + bịx bo = 36.465 - 1.082 b1 - 0.646 Use this to predict the number of situps a person who watches 2.5 hours of TV can do (to one decimal place)
- A red maple sapling was 3 feet tall when planted in 2010. Six years later, the tree was 18 feet tall. The growth rate of the tree is constant over time. Find a linear model for the height H (in ft) of the red maple t years after 2010. Let t = 0 represent 2010. H = What is the expected height (in ft) of the red maple in 2020? ftfind the 80th derivayive of y= (08 3XA regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-0.649 b=20.136 r2=0.488601 r=-0.699 Use this to predict the number of situps a person who watches 2.5 hours of TV can do (to one decimal place)
- A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-0.649 b=20.136 r2=0.488601 r=-0.699 Use this to predict the number of situps a person who watches 2.5 hours of TV can do (to one decimal place)A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: уах+ b a = -1.098 b = 37.154 r2 = 0.444889 r = -0.667 Use this to predict the number of situps a person who watches 11 hours of TV can do. situps = [one decimal accuracy]Contains data on brain mass in different species versus glia-neuron ratio, the latter being a measurement of brain metabolism as the glia provides the metabolic needs of the neurons. The relationship between THE LOGARITHM of the brain mass (in the third column) and Glia-neuron ratio (fourth column) appears linear and it is these two variables that we wish to analyze via linear regression. We would like to know if the human brain fits the trend from the other species. Towards this end we will perform the regression on all species EXCEPT humans (Homo sapiens). Again, throw out the human data from your analysis. You will however need the human numbers for some of the questions. The analysis to be performed is as follows: 1. Calculate the regression line (slope and intercept) 2. Perform an ANOVA test of the null hypothesis for zero slope. From this analysis, obtain SStotal, SSregression and SSresidual as well as the corresponding MS statistics. 3. Perform a t-test of the null…
- also compute the regression equation in which you predict Y using X as the predictor variableA regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=a+bx a=28.724 b=-1.299 r2=0.388129 r=-0.623 Use this to predict the number of situps a person who watches 7 hours of TV can do (to one decimal place) Submit QuestionPlease answer
