| University | Singapore University of Social Science (SUSS) |
| Subject | ANL251: Python Programming |
Assignment Brief:
(a) Compute and generate 20 normally distributed random numbers with a random seed of 1, mean of 100 and standard deviation of 10. Arrange time in a 2 by 10 matrix. Name this matrix xy_numbers.
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Categorise and extract numbers row-wise, that is. first_row .. land second_row — J. Let x takes the array of the first row and y takes the array of the second row. Display a scatter plot of y against x.
(b) Develop and implement a function to calculate mean square MO( by accepting 3 numeric list parameters: the regressed y value yeap,x_input and y_input.
Calculate linear regression on numbers and display the regressed line with an x-values span across 100 intervals evenly. from the minimum value to the maximum value of x data. Calculate the mean squared error, round off to two (S) decimal places.
(c) Calculate both quadratic and cubic regression on numbers and display the regressed curves, label them clearly for clarity. Calculate their mean squared errors, round onto two (2) decimal places.
(d) Since numbers have 10 columns of data, calculate degree 96 (= 10 • I) regression on numbers and display the regressed curve alone, label it clearly for clarity.
E) Criticise the limitation of getting predicted data from a regressed line/curve. List one (1). Explain the application of regression. List one (1). Present your answers with help of the Markdown answer for 4(e).
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