This means there's a 24% chance of finding the observed difference if our null hypothesis is true. (2-tailed) refers to our p-value of 0.24. Can we reasonably expect this difference just by random sampling 18 cases from some large population? Output - Test Statistics TableĮxact Sig. It turns out this holds for 12 instead of 9 cases. Since we've 18 respondents, our null hypothesis suggests that roughly 9 of them should rate ad1 higher than ad3. The percentage scales of our variables -fortunately- make this much less likely. This may be an issue with typical Likert scales. Output - Signs Tableįirst off, ties (that is: respondents scoring equally on both variables) are excluded from this analysis altogether. NPAR TESTS /SIGN=ad3 WITH ad1 (PAIRED) /MISSING ANALYSIS. SPSS Sign Test SyntaxĬompleting these steps results in the syntax below (you'll have one extra line if you included the exact test). If it's absent, just skip the step shown below. Whether your menu includes the E xact button depends on your SPSS license. We'll do so by reversing the variable order. We prefer having the best rated variable in the second slot. They're related (rather than independent) because they've been measured on the same respondents. The 2 Re lated samples refer to the two rating variables we're testing. The most straightforward way for running the sign test is outlined by the screenshots below. A very different distribution is unlikely under H0 and therefore argues that the population medians probably weren't equal after all. If our null hypothesis is true, then the plus and minus signs should be roughly distributed 50/50 in our sample.
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