1. ## Large t values

Hi,

I'm studying the use of certain teaching techniques in Korean high schools, specifically comparing students' perceptions of the frequency of use of traditional and modern teaching practices. I would expect very strong results based on my experience.

I have data from 5-point Likert scales, and having run paired samples t tests on it (I know there is controversy on whether parametric tests should be used with Likert data - but it's been okayed from 'up top') SPSS is giving me (as an example) -the following:

Korean teachers utilise traditional methodology significantly more frequently (M=4.06, SE=0.03) than they utilise modern methodology (M=2.18, SE=0.04), t(305)=34.42, p<.01. (in SPPS p actually shows up as .000)

I'm getting similar t and p values for the other comparisons too. My question is, that t value seems very large, so is this just telling me I have an extremely significant difference, or have I cocked something up somewhere??

Thanks!

2. ## Re: Large t values

Originally Posted by carruthers
Hi,

I'm studying the use of certain teaching techniques in Korean high schools, specifically comparing students' perceptions of the frequency of use of traditional and modern teaching practices. I would expect very strong results based on my experience.

I have data from 5-point Likert scales, and having run paired samples t tests on it (I know there is controversy on whether parametric tests should be used with Likert data - but it's been okayed from 'up top') SPSS is giving me (as an example) -the following:

Korean teachers utilise traditional methodology significantly more frequently (M=4.06, SE=0.03) than they utilise modern methodology (M=2.18, SE=0.04), t(305)=34.42, p<.01. (in SPPS p actually shows up as .000)

I'm getting similar t and p values for the other comparisons too. My question is, that t value seems very large, so is this just telling me I have an extremely significant difference, or have I cocked something up somewhere??

Thanks!
A large t would mean that there is only a small probability that your result was due to chance. The reason you got such a big t is because there was very little variability in your samples or large sample sizes (or both)...which is a good thing..it would signify that your means would be a good estimate of the population parameter.

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