Aaec 4302 advanced statistical methods in agricultural research
Download
1 / 10

AAEC 4302 ADVANCED STATISTICAL METHODS IN AGRICULTURAL RESEARCH - PowerPoint PPT Presentation


  • 85 Views
  • Uploaded on

AAEC 4302 ADVANCED STATISTICAL METHODS IN AGRICULTURAL RESEARCH. Chapter 14: F Tests. F Test. State the hypotheses Determine the value of F* Choose the level of significance ( α ) Use tables to determine F c Apply decision rule r df of the numerator (number of restrictions),

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' AAEC 4302 ADVANCED STATISTICAL METHODS IN AGRICULTURAL RESEARCH' - bruce-ellis


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Aaec 4302 advanced statistical methods in agricultural research

AAEC 4302ADVANCED STATISTICAL METHODS IN AGRICULTURAL RESEARCH

Chapter 14:

F Tests


F test
F Test

  • State the hypotheses

  • Determine the value of F*

  • Choose the level of significance (α)

  • Use tables to determine Fc

  • Apply decision rule

    r df of the numerator (number of restrictions),

    n-k-1 df of the denominator (k –number of regressors in the unrestricted model)


Most common applications of f test
Most Common Applications of F Test

  • Some of the coefficients are equal to zero:

    H0: β2 = β3 =0

    H1: β2 and/or β3≠ 0

    Models 1 and 3 in the table 14.1

  • All coefficients are equal to zero:

    H0: β1 = β2 = . . . =βk= 0

    H1: βj≠ 0 for at least one j, j = 1, . . .,k


Most common applications of f test1
Most Common Applications of F Test

  • F test for a set of dummy variables to be equal to zero:

    Table 14.1 model 5

    H0: β5 = β6 = β7 = 0

    H1: β5≠ 0 and/or β6≠ 0 and/or β7≠ 0

  • A single regression coefficient is equal to zero:

    H0: βj = 0

    H1: βj≠ 0


Most common applications of f test2
Most Common Applications of F Test

  • Testing a hypothesis that specifies a relation among coefficients:

    H0: β1 = β2

    H1: β1≠ β2

    CONi = β0 + β1 LABINCi + β2 PROPINCi + ui

    CONi = β0 + β1 TOTINCi + ui , r=1


The chow test
The Chow Test

  • Test for equality of coefficients

    Model 3 in table 14.1

    The unrestricted form, allowing for differences, consists of two estimated regressions 3 one for blacks and one for whites

    SSRu = 0.6713+16.9793=17.6506

    Restricted form is regression 3 in table 14.1


The chow test1
The Chow Test

  • In time-series data Chow test is the test for structural stability

    H0: coefficients are the same in both periods

    H1: Coefficients are different in both periods

    LNMi = β0 + β1LNGNPi + ui

    Two time periods: 1956-1970 and 1971-1980

    H0: β01 = β02 and β11 = β12

    H1: β01≠ β02 and β11≠β12


F test example
F-Test Example

Ŷi = 474.05 + 1.46X1 +26.32X2

Test:

H0: β1 = β2 =0

Ha: β1 and/or β2≠ 0


F test example1
F-Test Example

RSS = 1687891.751

SSE = 4086450.184


F test example2
F-Test Example

F* = 27.06

Fcr2,131 at α=0.01≈ 4.78

Since the calculated F* is greater than the Fcr => you are 99% sure that both X1 and X2 have statistical impact on Y.


ad