interpolation approach of estimation is
a) probabilistic
b) non probabilistic
c) non mathematical
d) all the above
interpolation approach of estimation is non probabilistic
estimation under interpolationa) is less accurate than extrapolation b) is an accurate as extrapolationc) is more accurate than extrapolationd) none of the above
interpolation and extrapolation are same in the sense that a) both determine most likely estimateb) both result into the same value c) both are complementary to each other d) all the above
interpolation is not affected by a) sudden fluctuations b) irregular variations c) unforeseen events d) none of the above
interpolation is a technique for a) obtaining most likely missing links b) finding relationship between two variables c) comparing the two series d) none of above
interpolation means estimating a value which lies a) within the given range of arguments b) outside the given range of arguments c) outside the range of the independent variable d) none of the above
The most common probabilistic sampling approach is: A. simple random sampling B. convenient sampling C. complex sampling D. error sampling
please answer both questions → XC A D Question 13 4 pts Which one of the following statement(s) is (are) not correct? Risk analysis is primarily used to: a) Find the opportunity with the greater ROI (return on investment) potential. b) Find the opportunity with the greater risk. c) All of the above. d) Describe the range of possible outcomes and their consequences. c) All of the above. D Question 14 4 pts Which one of the following methods is...
Define: a. Model, Variables, Parameters b. Constraints in linear programming c. Mathematical relationships known with certainty and probabilistic conditions(risk model)
Year Population 1900 200507 1910 430980 1920 732016 1930 1265258 1940 1394711 1950 1451277 1960 1424815 1970 1471701 1980 1168972 1990 1203789 2000 1332650 2010 1385108 the census populations of the Bronx from 1900 to 2010 is given above. Estimate the Bronx's 2005 population using the following methods: (a) Linear interpolation interp1 (year, population, 2005)) (b) Polynomial interpolation of just the last three censuses (polyval and polyfit) (c) Polynomial interpolation of all the censuses (d) Second-degree polynomial regression (not interpolation;...
3D Cubic B-Spline Interpolation and Error Estimation Theme: Implement and study 3D Cubic Spline Interpolation Input: a set of points in 3D space (data(x,y,z)) Output: Spline, Spline data points and error, 3D graph that shows the original points and the Spline The major steps involved in the B-Spline Fitting and Error Estimation are as mentioned below: 1- Sample the data points from input data. 2- Interpolate to find the position of control points. 3- Use the B-Spline basis function to...