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· Write a thorough statement as to the variables used and the reason you think these variables may or may not be related.
· Clearly identify the explanatory and response variables.
· Clearly define the population from which the sample data is being drawn.
· Specifically state how the sample was selected.
· Report the raw data.
· Draw a scatter plot for the data values. (Excel is a great tool for entering data and plotting a scatter plot.)
· Write a clear and concise statement analyzing the scatter plot.
· Compute the value of the correlation coefficient (r). (This computation may be done using your calculator or computer.)
Where denotes the usual cross product of vectors. Sow that L is a Lie algebra and determine its structure constants relative to the standard basis for R3.
Use 4th order Runge-Kutta Method with step size h =0.2 and h =0.1 to find y(2) and sketch all the solutions on the interval [1, 2] with appropriate legend for comparison.
What general conclusions can you reach about the relationship between the relative sizes of the two masses and the corresponding reduced mass?
Explain what each of the following mathematical statements mean in regard to the graph of f(x).With your explanation, include a DIAGRAM for each part.
explain why the typical hypothesis that analysts want to test is whether a particular regression coefficient (B) is equal to zero (H0: B = 0) versus whether that coefficient is not equal to zero (H1: B ≠ 0).
Plot a graph of the signal f(t) and determine the first four terms of the Fourier series for 1(t).
Do the sample data indicate a significant change in depression (2-tailed test)? Test with alpha = .05, 2-tailed test
Draw a decision tree for this problem and what is the optimal decision for this investor and what is the EMV for this decision?
Analysis of the climograph, identifying the climate zone by name and Koppen-Geiger classification and a discussion of the controls on the climate that produce this pattern.
Linear programming applied to Aggregate Production Planning of Flat Screen Monitor
Discrete-time model for an economy
the purpose of this paper is to develop a new linear programming for an aggregate production planning of flat panel
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