[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

From |
"Ada Ma" <[email protected]> |

To |
<[email protected]> |

Subject |
st: Re: RE: need mini tutorial in ttest result reading |

Date |
Tue, 6 May 2003 17:18:38 +0100 |

Many thanks for the suggestions. I have printed out the Box paper and I'm going to read it. Honestly. Ada Ma Department of Economics University of Aberdeen, Scotland [email protected] ----- Original Message ----- From: "Nick Cox" <[email protected]> To: <[email protected]> Sent: Monday, May 05, 2003 5:33 PM Subject: st: RE: need mini tutorial in ttest result reading > Ada Ma > > > > I've been staring at the results for days and read the > > related part of the > > Stata manual 10 times or more and I'm still confused. I > > want to find out > > whether the results tell me that I can reject these hypostheses: > > > > H0: mean(he) = mean(hexo) [HA: mean(he)~=mean(hexo)] > > H0: sd(he) = sd(hexo) [HA: sd(he)~=sd(hexo)] > > > > Does the following results tell me that I can can reject > > both HA and thus > > accept H0? Is it that the larger is the P figure, the more > > likely I'll have > > to accept HA? > > > > > > . ttest LFShe=LFShePOT if regwk==1, unpaired > > > > Two-sample t test with equal variances > > > > ------------------------------------------------------------ > > ------------------ > > Variable | Obs Mean Std. Err. Std. Dev. > > [95% Conf. > > Interval] > > ---------+-------------------------------------------------- > > ------------------ > > LFShe | 560 9.520129 .2146156 5.078732 > > 9.098578 > > 9.941681 > > LFShePOT | 560 8.862436 .2016839 4.772713 > > 8.466285 > > 9.258587 > > ---------+-------------------------------------------------- > > ------------------ > > combined | 1120 9.191283 .1475172 4.93687 > > 8.901841 > > 9.480724 > > ---------+-------------------------------------------------- > > ------------------ > > diff | .6576928 .2945102 > > .0798378 > > 1.235548 > > ------------------------------------------------------------ > > ------------------ > > Degrees of freedom: 1118 > > > > Ho: mean(LFShe) - mean(LFShePOT) = diff = 0 > > > > Ha: diff < 0 Ha: diff ~= 0 > > Ha: diff > 0 > > t = 2.2332 t = 2.2332 > > t = 2.2332 > > P < t = 0.9871 P > |t| = 0.0257 P > > > t = 0.0129 > > . sdtest LFShe=LFShePOT if regwk==1 > > > > Variance ratio test > > > > ------------------------------------------------------------ > > ------------------ > > Variable | Obs Mean Std. Err. Std. Dev. > > [95% Conf. > > Interval] > > ---------+-------------------------------------------------- > > ------------------ > > LFShe | 560 9.520129 .2146156 5.078732 > > 9.098578 > > 9.941681 > > LFShePOT | 560 8.862436 .2016839 4.772713 > > 8.466285 > > 9.258587 > > ---------+-------------------------------------------------- > > ------------------ > > combined | 1120 9.191283 .1475172 4.93687 > > 8.901841 > > 9.480724 > > ------------------------------------------------------------ > > ------------------ > > > > Ho: sd(LFShe) = sd(LFShePOT) > > > > F(559,559) observed = F_obs = 1.132 > > F(559,559) lower tail = F_L = 1/F_obs = 0.883 > > F(559,559) upper tail = F_U = F_obs = 1.132 > > > > Ha: sd(1) < sd(2) Ha: sd(1) ~= sd(2) > > Ha: sd(1) > sd(2) > > P < F_obs = 0.9290 P < F_L + P > F_U = 0.1420 P > > > F_obs = 0.0710 > > I am not clear whether you intend some kind of joint test or > if one test is considered as prerequisite to another. > > Setting that aside, according to many statisticians, > your question(s) cannot be answered because you > don't tell us what your alternative hypothesis was > (e.g.) before you carried out the t test, i.e. > two-tailed or one-tailed, etc. And according to the > same conservative view your test is dubious if not > meaningless without that being sorted out in > advance. > > However, informally, I imagine most users > would feel encouraged, if not obliged, to reject the > null hypothesis of no difference between means and accept > instead the alternative hypothesis of a positive difference, on this > evidence, and at a level of 0.05. Clearly, if you use a different > threshold, the decision may vary (notably, one of 0.01). > > This year marks the 50th anniversary of George > Edward Pelham Box's paper in Biometrika which pointed > out that the t test for means is in > practice much more robust than a test comparing variances. > He used some more colourful language: if I recall > correctly, he compared the common practice of F test > before t test to putting out > to sea in a dinghy to see if it was safe for an > ocean liner to leave port. > > Having said that, > > 1. Looking at confidence intervals is often preferable. > > 2. I'd still look at a graph to compare the > whole of the distributions, e.g. -qqplot-. > > Not what you asked, but possibly relevant > to the scientific problem which presumably > underlies this. > > Nick > [email protected] > * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: RE: need mini tutorial in ttest result reading***From:*"Nick Cox" <[email protected]>

- Prev by Date:
**st: Weibull simulation-parametrization** - Next by Date:
**Re: st: Weibull simulation-parametrization** - Previous by thread:
**st: text editors and Stata FAQ** - Next by thread:
**st: New package -bygap- on SSC (and updated -sencode-)** - Index(es):

© Copyright 1996–2024 StataCorp LLC | Terms of use | Privacy | Contact us | What's new | Site index |