所有大题(All big questions).doc

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所有大题(All big questions)

所有大题(All big questions) 1, the economics, econometrics and statistics, mathematical statistics between disciplines. The econometric study focuses on the quantitative aspects of the statistics on how to collect and analyze the data of the subject, and uses econometrics economic statistics provided data to estimate the quantitative relationship between economic variables and verified. Mathematical statistics is a mathematical science, can be used in the economic field, but also can be used in other fields; econometrics is only limited to the economic field, the process of establishing econometric model, is a process of comprehensive application of theoretical, statistical and mathematical methods, econometrics is the unification of economic theory, statistics and mathematics three. 2, the econometric model which used? Structure analysis, economic forecasting and policy evaluation, testing and development of economic theory The establishment and application of the main steps of the econometric model, the 3 According to economic theory, econometric model; data collection; parameter estimation; model test; application of econometric model. 4, the econometric model from the aspects of inspection The economic significance of inspection; statistical criterion; econometric model to predict the test criterion; 5, econometric application data is how to classify Four classification: time series data; cross section data; mixed data; dummy variable data. 6, in the econometric model, why there is random error Random error is an indispensable part in econometric modeling. Random errors due to the following aspects: the error caused by factors are ignored in the model variables; measurement error; random factors. 7 basic assumptions of the classical linear regression model is what The assumption of zero. Remember in a given XT condition, mathematical expectation of random errors (mean) 0, E (UT) =0. The same difference assumption. The error variance of T and UT is a constant. The no

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