Need help finishing the regression equation with the following:  Y=Residents' Preference B=Size of sector budget, sector budget, and individual trust as Independent Variables.  I'm using Jamovi software, but the need to create the equation with information above.  Thanks,

Develop an estimated multiple regression equation that relates risk of a stroke to a person's age, systolic blood pressure and whether the person is a smoker.  x1=persons age x2systrolic blood pressure x3=whether person is a smoker or non smoker

Imagine Daenerys Targaryen as a researcher concerned with the dragon species. The people of Westeros believed that dragons were decreasing in size due to captivity. Dragon size was normally measured as wingspan (meters) and captivity was normally measured in years. Daenerys used archival data and determined that the relationship between these two variables could be explained using the following regression equation: y-predicted = 453 - 2.5xInterpret this equation (i.e. What is its purpose? What is the intercept? What is the slope? What does it mean for dragons in Westeros?).

You are conducting a multiple regression analysis to determine if there is a linear relationship between y, the number of applications to in-state universities and two factors: ×1, the state's unemployment rate and ×2, the average grant provided to in-state students. Ten observations are available. The analysis produced the estimated regression equation below. y = 6.5 + 2.2×1 + 4.6×2 The standard error for the intercept, unemployment rate are 9.34, and 1.23, respectively. Is the coefficient for the unemployment rate variable statistically significant at the 5% significance level? Explain. A) No, since stat = 1.39 for this coefficient, which is less than 2.365. B) No, since the p-value for this coefficient is .072, which is greater than 05 C) None of these D) No, since the p-value for this coefficient is .072, which is greater than .05

What needs to change in an overall problem if one wants to use linear regression?

A real estate company wants to study the relationship between house sales prices and some important predictors of sales prices. Based on data from recently sold homes in the space, the following variables are used in a multiple regression model. y sales price (in thousands of dollars) x₁ = total floor area (in square feet) X₂= number of bedrooms x3² distance to nearest high school (in miles) The estimated model is as follows. y=121 +0.083x₁ +23x₂ - 4x3 Answer the questions below for the interpretation of the coefficient of x₁ in this model. (a) Holding the other variables fixed, what is the average change in sales price for each 100-square-foot increase in floor area? dollars (b) Is this change an increase or a decrease? increase decrease X Ś

The linear regression equation for the data from the number 2 is y=.27x+5.82.  Describe the slope of the linear best-fit equations.

Flying twice as farA flight from Los Angeles to ABQ is about 2 hours but is 670.2 miles.A flight from San Jose to Chicago is 4 hours but is 1859.0 miles.Can anyone explain why the travel time from San Jose to Chicago is notlonger and closer to 5.75 hours?If the distance increase by 2, shouldnt the time increase by a factorof 2 as well?1. Write a linear model for this question. Takeoff and landing will take a fixed amount of time. Actualtravel in the air will take time proportional to the distance traveled. Think about which of thevariables (time and distance) is the independent variable, and identify the slope and intercept withtheir units.2. Use the data in the quotation to estimate the two constants in your linear model.

What are the interpretations of the Y intercept and the slopes in a multiple regression model?

The following linear regression model can be used to predict ticket sales at a popular water park. Ticket sales per hour = - 631.25 + 11.25(current temperature in °F)23) Choose the statement that best states the meaning of the slope in this context. A)  The slope tells us that a one degree increase in temperature is associated with an average increase in ticket sales of 11.25 tickets. B)  The slope tells us that high temperatures are causing more people to buy tickets to the water park. C)  The slope tells us that if ticket sales are decreasing there must have been a drop in temperature. D)  None of these