Examination of Econometrics (option 4)


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Description Examination of Econometrics (option 4)
Objective 1
State share of income directed to the increase of savings in deposits in the total amount of per capita income,%, at an average monthly salary, ths. Rub., X
Bryansk 6.9 289
Vladimir 8.7 334
Ivanovo 6.4 300
Kaluga 8.4 343
Kostroma 8.1 356
Orel 6.5 289
Ryazan 9.1 341
Smolensk 6.4 327
Tverskaya 9.3 357
Tula 8.2 352
Yaroslavl 10.7 381
Task:
1. Construct a field correlation and specify a hypothesis about the form of communication.
2. Calculate the parameters of regression equations: linear, power, exponential and equilateral hyperbola.
3. To assess the closeness of the relationship with the help of performance correlation and determination.
4. Writing using the secondary (general) comparative assessment of the elasticity coefficient power factor due to the result.
5. Assess using approximation error of average quality equations.
6. Use FFisher criterion to assess the statistical reliability of the results of the regression modeling. From the values \u200b\u200bof performance, calculated in points. 4, 5 and this paragraph, select the best regression equation and give its rationale.
7. Calculate the predicted value of the result, if the predictive value of the factor will increase by 10% from its average level. Determine the confidence interval for the forecast level of significance = 0,05.
Task 2
From the combination of 25 enterprises of the concern we study the dependence of consumption of materials y (t) of the installed power of labor x1 (kWh per worker.) And the volume of output x2 (thousand units). Data are presented in the table below:
Symptom Mean value Standard deviation Paired correlation coefficient
y 12,0 2,0 r_ (yx_1) = 0,52
x_1 4,3 0,5 r_ (yx_2) = 0,84
x_2 10,0 1,8 r_ (x_1 x_2) = 0,43
Task:
1. Build a multiple regression equation and explain the economic meaning of its parameters.
2. Locate the private and multiple correlation coefficients.
3. Evaluate the significance of the regression equation using FFisher criterion.