Xy16212683345822 861 966Use exponential regression to find an exponential function that best fits this daf(x) = 573.2 (1.1057)O LinearUse linear regression to find an linear function that best fits this data.g(x) = 543.8667 (80.9429)61010ExponentialXOf these two, which equation best fits the data?

We need to determine the exponential equation and linear equation that best fits the data. We also…

Answered: X y 1 2 621 683 3 4 822 861 Use…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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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=-0.926 b=22.103 r2=0.481636 r=-0.694 Use this to predict the number of situps a person who watches 7.5 hours of TV can do (to one decimal place)
A regression was run to determine if there is a relationship between hours of study per week (x) and the final exam scores (y). The results of the regression were: y=ax+b a=6.59 b=21.22 r²=0.599076 r=0.774 Use this to predict the final exam score of a student who studies 7 hours per week, and please round your answer to a whole number.
An investment appreciates 2% per year. Originally $5000 is invested. What is an equation for the years since the money is invested as a function of the investment's worth? Ot = log(F/5000)/log(0.02 t = log(F/5000)/log(1.02) Ot = log(F/5000)/log(0.98) t = log(F/5000)/log(-1.02)
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=-0.971 b=21.794 r²-0.872356 r=-0.934 Use this to predict the number of situps a person who watches 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= -0.889 b=32.071 r2=0.505521 r= -0.711 Use this to predict the number of situps a person who watches 5 hours of TV can do (to one decimal place)
Smith is studying the relationship between length (X) and weight (Y) of infants. Please help him fit an exponential growth model to find the relationship between length and weight. Write down the model and explain how to fit the model (i.e., how to estimate regression coefficients) and what the intercept is for the relationship between X and Y (in symbolic form).
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=-1.34 b=36.954 r2=0.966289 r=-0.983 Use this to predict the number of situps a person who watches 5 hours of TV can do (to one decimal place)
The income of farmers depends on various factors. To predict the income of the next year, a study was undertaken and data was gathered considering as many as possible factors that might influence the yearly income. Regression methods are used to create such a prediction function, that is, we want to predict the profit for the next year. The following were determined. X₁ = SIZE - farm size recorded × 1000 hectares X₂ AGE - how long the farm has been in operation in years X3 = RATIO - the ratio of land size to field size recorded as 0.5, 0.75, 0.8 and 0.9 X4 = METHOD - rotational and non rotational method of planting Ŷ INCOME the income per year recorded in × R 1 000 000.00 The partial dataset is as follows INCOME Y 1.3 2.4 3.2 1.5 2.1 a. C. Standardized Residual Sample Quantiles 15 1.0- 0.8- 0.6- 0.4- 0.2- 0.0- 20 SIZE X₁ 25 5 8 2 1.2 1.5 Predicted Theoretical Quantiles. 45 AGE X₂ 1.1. The analyst did some exploratory analysis and below are some of the residual plots he constructed.…

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