What is the equation of the least-squares regressionAn analysis of the decay of 10 grams of an unstableelement over time was completed and is displayed in theline?computer output.Element = 2.305 - 0.101 In(Time)%3DRegression Analysis: In (Element) versus TimePredictorCoefSE CoefIn(Element) = 2.305 0.101(Time)Constant2.3050.021109.760.000Time-0.101 0.0007-132.990.000In(Element) =- 0.101 + 2.305(Time)S=0.0079R-Sq 0.99R-Sq (adj)=0.999O In(Time) = -0.101 + 2.305(Element)

Given Information: Consider the given regression analysis output:

An analysis of the decay of 10 grams of an unstable element over time was completed and is displayed in the What is the equation of the least-squares regression line? computer output. Element = 2.305 - 0.101 In(Time) Regression Analysis: 1n (Element) versus Time Predictor Coef SE Coef In(Element) = 2.305 0.101(Time) Constant 2.305 0.021 109.76 0.000 Time -0.101 0.0007 -132.99 0.000 R-Sq (adj)-0.999 In(Element) = -0.101 + 2.305(Time) s=0.0079 R-Sq 0.99 In(Time) = -0.101 + 2.305(Element)

An analysis of the decay of 10 grams of an unstable element over time was completed and is displayed in the What is the equation of the least-squares regression line? computer output. Element = 2.305 - 0.101 In(Time) Regression Analysis: 1n (Element) versus Time Predictor Coef SE Coef In(Element) = 2.305 0.101(Time) Constant 2.305 0.021 109.76 0.000 Time -0.101 0.0007 -132.99 0.000 R-Sq (adj)-0.999 In(Element) = -0.101 + 2.305(Time) s=0.0079 R-Sq 0.99 In(Time) = -0.101 + 2.305(Element)

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

A multiple regression model was fit to predict domestic gross for movies based off of the production budget, opening weekend gross and number of stars. The overall F test p-value equals 0.252. What conclusion can you make at alpha = 0.05? All of the variables contribute to the model. At least one of the variables contributes to the model. O None of the variables contribute to the model.
A linear regression model has been estimated for the variables Y="monthly consumption of veal (kg)", X1="monthly monetary household income (thousand EUR)" and X2="household size (number of members)" using data for a random sample of 80 households. The following results have been obtained: b0=0.3 b1=0.5 b2=0.7 R-sq=0.9 R=0.95，Interpret the value of regression coefficient b2.
s is the typical amount by which the (BMI Change, Depression Score Change) value what is predicted using the least squares regression line.
A least squares regression line was calculated to relate the length (cm) of newborn boys to their weight in kg. The line is weight=−5.82+0.1601 length. A newborn was 48 cm long and weighed 3 kg. According to the regression model, what was his residual? What does that say about him?
What is the mathematical representation for the multiple logistic regression model in photo?
Write the equation of the least-squares regression line. Use the full accuracy shown in the calculator output (do not round your answers).
The relationship between rainfall and the probability of flooding is given by the logistic regression p = 1 1+e-(a+br) Use the following data and regression method with a confidence level of 95% to select all true expressions about the model. r= Rainfall (mm) 200 250 280 300 325 350 380 400 p= Probability of flooding 0.02 0.09 0.12 0.3 0.4 0.7 0.9 0.93 Select one or more: O 1. The correlation of p and r is a strong negative correlation. 2. The estimation of p at r=360 is 0.78 3. The maximum error for the data happens at r=325 4. a = 10.8431 and b = -0.0337 5. R-squared=0.99
Write the multiple regression equation for miles per gallon as the response variable. How might the car rental company use this model?
The least-squares regression equation is y = 689.9x + 14,803 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7256. Complete parts (a) through (d). (a) Predict the median income of a region in which 20% of adults 25 years and older have at least a bachelor's degree. (Round to the nearest dollar as needed.) . TOLED dian Income Media 55000- 20000- 15 20 25 30 35 40 45 50 55 60 Bachelor's 96 Q
Please help asap
To predict blood alcohol content of a student who drank 5 beers will be about?
What does this data mean if the values are logistic regression analysis of presence of sarcopenia as the dependent variable OR (95% CI) p-value 3.069 (1.42-6.62) 0.004