- Arts & Culture 4533
- Books in Foreign Languages 199
- Business & Economics 4688
- Computers 2346
- Dictionaries & Encyclopedias 676
- Education & Science 80139
- Abstracts 1271
- Astrology 14
- Astronomy 13
- Biology 40
- Chemistry 3027
- Coursework 3777
- Culture 31
- Diplomas 2786
- Drawings 1704
- Ecology 31
- Economy 328
- English 1253
- Entomology 2
- Ethics, Aesthetics 28
- For Education Students 21485
- Foreign Languages 115
- Geography 20
- Geology 17
- History 232
- Maps & Atlases 42
- Mathematics 6112
- Musical Literature 5
- Pedagogics 221
- Philosophy 190
- Physics 13015
- Political Science 131
- Practical Work 96
- Psychology 474
- Religion 51
- Russian and culture of speech 103
- School Textbooks 70
- Sexology 67
- Sociology 53
- Summaries, Cribs 935
- Tests 21467
- Textbooks for Colleges and Universities 208
- Theses 185
- To Help Graduate Students 19
- To Help the Entrant 111
- Vetting 343
- Works 57
- Информатика 10

- Engineering 3245
- Esoteric 1167
- Fiction 3147
- For Children 417
- House, Family & Entertainment 2537
- Law 2890
- Medicine 1234
- Newspapers & Magazines 336
- Security 312
- Sport, Tourism 996
- Website Promotion 678

# Test econometrics

Refunds: 0

Uploaded:

**11.08.2013**

Content: 30811175157600.rar (40,94 kB)

# Description

1. As a parameter called the linear regression equation to stand at factor?

coefficient of elasticity

the coefficient of determination

the regression coefficient

correlation coefficient

coefficient of variation

2. Main factors stepwise selection procedures in multiple regression equation is:

sequential removal procedure

sequential evaluation process

Sequential coupling procedure

serial replacement procedure

Serial averaging procedure

3. If a growth factor variable values \u200b\u200bgrow variance estimates of the parameters of the regression equation, it is called:

autoregression

homoscedasticity

autocorrelation

ergodicity

heteroskedasticity

4. What point are excluded from the time series smoothing procedure

standing at the beginning of the time series

facing both the beginning and end of a time series

standing at the end of the time series

5.KMNK applicable in the case

exactly identified model

unidentifiable models

sverhidentifitsiruemoy model

Whether to apply the method of least squares to calculate the parameters of the exponential dependence?

apply after its reduction to a linear form by integrating

yes

apply after its reduction to a linear form by potentiation

no

apply after its reduction to a linear form by taking the logarithm of correlation coefficient of -1 means that

between variables there is a functional relationship

The situation is not defined

linear relationship between the variables missing

between variables there is a linear correlation

The wrong choice of functional form, or referred to the explanatory variables

forecast errors

heteroskedasticity

error of specification

If the correlation coefficient is negative, the linear model

x decreases with the decrease in

decreases with increasing x in

with increasing x increases from

With the exclusion of uninformative factor value previously calculated coefficient of multiple determination:

significantly reduced

increase significantly

will not change

By using analytical smoothing of the time series is plotted a number of levels from time to time, which is called:

trend

trend

lag

extrapolation

If the time series have trend and cyclical fluctuations, then:

you can just simulate the trend

to exclude random component, and then simulate the trend

to exclude cyclical component, and then simulate the trend

MNCs can not be used under conditions (multiple answers):

lack of effect of multicollinearity

close connecting factor with the result

small volume sets

weak link factor with the result

heterogeneity characteristic values;

the effect of the presence of multicollinearity

a small number of signs

To what extent it changes the coefficient of determination

-1 to 0

0 to 1

-1 to 1

from 0 to 10

If the autocorrelation coefficients of all orders are statistically insignificant, the series includes:

only a random component

random component or strong linear trend

Only a strong linear trend

Only a strong non-linear trend

random component or a strong non-linear trend

As interpreted in a linear model regression coefficient?

coefficient of elasticity

absolute growth rate

relative growth rate

# Additional information

How many points is preferable to take to calculate the smoothed value

any

odd

an even

Direction connection statistics classified ......

linear and nonlinear

strengths and weaknesses

legitimate and arbitrary

forward and backward

What are the time series are called interval?

levels which reflect the value of the phenomenon under study at any given time

levels which characterize the phenomenon under study for certain time intervals

levels which characterize the phenomenon under study by means of medium or relative values

Multiple correlation coefficient can be:

0 to 1

any less than zero

any positive

-1 to 0

-1 to 1

In the presence of inverse linear functional relationship between quantitative traits X and Y, the correlation coefficient r = ....

-1

-0.6

0.6

0.9

+1

An index of correlation equal to the value of the linear correlation coefficient if the dependence

Logistics

Exponential

Parabolic

linear

The coefficient of determination is the share .......

intra-group variance in the total variance

Intergroup variance in the residual

Intergroup variance in total

intraclass variance in residual dispersion

As a result of regression analysis exploring the function describing ......... indicators.

ratio

structure

interconnection

growth rate

growth

If effective sign influences two factors during the regression analysis build ....... model.

Multivariate

Univariate

Complex

Pair

The square of the coefficient indicates the proportion of the variance of a random variable, due to variation of another

multiple correlation coefficient

the coefficient of determination

Pair correlation coefficient

partial correlation coefficient

An empirical correlation ratio determines the ... ..

variation feature together

connection direction

variation factor underlying the grouping

close connection

variation of other factors, excluding the factor group

In the analysis of time series containing the seasonal component, the easiest way is the method of its calculation:

average shifted

autoregressive average

MA

arithmetic average

chronological average

If the time series is represented by the product of its components, the model number of the called

multiplicative

variativnoj

attributive

additive

In practice, the presence of multicollinearity is usually judged on a matrix of pairwise correlation coefficients. If one of the pair correlation coefficients between the factor variables more ..., it is considered that there is multicollinearity.

0.5

0.3

0.7