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can someone give me an example of what they mean about this problem. I have to come up with a real-world example where we can apply the concept learned within our chapter that the data could be linear which it talks about solving equations using the method of least squares within linear functions. then explain it but i have no idea how to set it up. I think it would be something of companies data.But i have no clue how...
can someone give me an example of how can one apply any concept (determining the slope and equation of a line, applying linear functions to mathematic applications, solving equations using the method of least squares) in order to decide if data are linear.Since this is not my area of expertise, I searched Google under the key words "slope equation line" to get these possible sources: http://www.wtamu.edu/academic/anns/mps/math/mathlab/int_algebra/int_alg_tut15_slope.htm http://www.purplemath.com/modules/slope.htm http://id.mind.net/~zona/mmts/functionInstitute/linearFunctions/lsif.html http://www.mathwords.com/p/point_slope_equation_of_a_line.htm http://en.wikipedia.org/wiki/Slope You can find the remaining information you desire, if you...
Can someone help me do an example like this one. State the application, give the equation of the quadratic function, and state what the x and y in the application represent. Choose at least two values of x to input into your function and find the corresponding y for each. State, in words, what each x and y means in terms of your real-life application. Please see the following example. You may use other variables besides x and y, such...
Can someone help me with this problem? I think I am missing a step somewhere and I cannot figure out where. Find the slope and y-intercept by writing the equation in slope intercept form and graph. 3x+y=-2 Would you consider the y a 1? Thanks
You want to estimate the slope of the relationship between y and x given by the usual linear regression equation: yi = ß0 + ß1 xi + ui i = 1, ..., n observations. Youare just about to run a plain vanilla OLS regression as your good old friend Mr. Critic (oh no...) enters the room and proposes a better idea. He says: “Running OLS isordi...nary and boring. Let’s estimate ß1 using a new estimator that I just invented. You...
9 14 marks] An id (independent and identically distributed) sample can be considered a linear model of the form:-Д +E, where ε, ~ indep(0,σ2). For this model we can use Least Squares Estimation to estimate the line E(Y) with the line . For this model, derive the Least Squares Estimator of 9 14 marks] An id (independent and identically distributed) sample can be considered a linear model of the form:-Д +E, where ε, ~ indep(0,σ2). For this model we can...
2.)First, create function[a,b]=linear_ls_xxx(x,y) as defined below. Note thatthis is a strictly linear operation, any log or semilog processing is done before the function is called.function[a,b]=linear_ls_xxx(x,y)%function[a,b]=linear_ls_xxx(x,y)% This function creates a linear least-squares estimate of the% slope (a) and y-intercept (b) given a set of input data (x,y).% The form of the estimate is y_hat = a*x +b, where y_hat is the% least-squares estimate of y% Calling parameters%... (you fill in)% Returned parameters%... (you fill in)
I'm trying to follow a research paperThe paper shows an equation to minimize. That makes perfect sense. Then, the paper says: "The optimal solution to the least squares problem [above] is found by differentiation as a solution of a linear system of equations."I am very familiar with traditional linear algebra least squares:y = xb + esolve for coefficients b by:b = (x^T * x)^-1 * x^T * yI understand the equation to be minimized but I don't understand the formulas...
You are planning to estimate a short-run production function for your firm, and you have collected the following data on labor usage and output. Labor usage output 3 1 7 2 9 3 11 5 17 8 17 10 20 15 24 18 26 22 28 21 30 23 (a) Does a cubic equation appear to be a suitable specification, given this data? You may wish to construct a scatter diagram to help you answer this question. (b) using a...
Q. Explain the logic of the ordinary least squares (OLS )method.A. The ordinary least squares method(or OLS method for short) is used to estimate aregression so as toensure the best fit.‘‘Best’’ fit in this case means that wehave selected the slope and intercept so that ourresiduals are as small aspossible.Q.How are the least squares formulas for the slopeand intercept derived?A.Q. What sums are needed tocalculate the least squares estimates?A.