Is 0 a valid value in a Likert scale? I have carried out my pilot study on language learning motivation using a 6 point Likert scale but from 0 (strongly disagree) to 5 (very much agree). I noticed a colleague in his survey used 1 to 6. Will my computed variables (sum and mean) be the same as if I had used 1 to 6? Is it normally recommended to not use a 0 for some reason? I am new to SPSS but have managed to do most of what I need to do but I'm now worrying my values are 'distorted'. I don't understand how SPSS adds a 0 into an equation. 
 A: Let me make a couple of points.  First, if you just have 1 question, you don't technically have a likert scale, but just an ordinal rating.  At any rate, I can't see as how there will be any meaningful difference.  This is just a linear shift.  This will neither make a difference whether you use an ordinal analysis like ordinal logistic regression or a Mann-Whitney U test, or a more standard option like OLS regression or a t-test.
A: I must partially disagree with @MichaelChernick. While answers to a single Likert question (whether 0 to 5 or 1 to 6 or whatever) are clearly ordinal, usually there is a sum of several Likert scale items. At some point, the number of possible values becomes so high that it is essentially continuous. 
As you know (but the poster of the question may not) OLS regression does not assume that the dependent variable is normally distributed, only that the errors (as estimated by the residuals) are. 
If we sum a bunch of Likert items, do we know that the intervals are really equal? No, not really.  But do we know that for, say IQ? Or even income? Is the difference between an IQ of 130 and 140 the same as 100 and 110? Does that question even make sense? What about a \$10,000 raise for someone who makes \$10,000 vs. $100,000 per year?
I wrote a whole blog post on this.
In addition, it's not clear to me whether this Likert scale is going to be a dependent or independent variable. 
A: In following up on @caracal's reference suggestions, I found an almost-direct answer (no, these two rating systems are not equivalent if presented as number options to respondents) from Schwarz, Knäuper, Hippler, Noelle-Neumann, and Clark (1991). They present data on responses to the question, "How successful have you been in life, so far?" One version gave rating options from 0–10 to 480 participants; the other version had options from (-5)–(+5) with zero as the midpoint, and was seen by 552 participants. The endpoints were labelled “not at all successful” and “extremely successful” in both versions. "Undecided" was also an option on both. Here's how things shook out:

$$\begin{array}{ccc|ccc}&\text{0–10 Scale}&&&-5\text{ to +5 Scale}&\\\hline\small\text{Scale Value}&\small\text{Percentage}&\small\text{Cumulative}&\small\text{Scale Value}&\small\text{Percentage}&\small\text{Cumulative}\\\hline0&...&...&-5&1&1\\1&...&...&-4&...&1\\2&2&2&-3&1&2\\3&5&7&-2&1&3\\4&7&14&-1&1&4\\5&20&34&0&9&13\\6&14&48&+1&9&22\\7&20&68&+2&23&45\\8&20&88&+3&35&80\\9&6&94&+4&14&94\\10&3&97&+5&4&98\\\text{Undecided}&3&100&\rm{Undecided}&2&100\end{array}$$

Quite different, clearly! They also report $\chi^2(10)=105.1,p<.0001$ for this difference. Of course, this difference won't appear if the difference is only behind the scenes in terms of how you code responses, not visible to participants as a way for them to provide responses.

There are simple survey design methods that allow one to avoid worrying about the psychological effects of equating rating anchors with numbers. Basically, you can just avoid using numbers! E.g.: 


*

*Allow respondents to check cells in a table corresponding to their answer preference: each row can be a different item, and each column can be labeled with your rating anchor, or vice versa – no numbers involved. Here's how that might look (if one were to answer wisely):
$\begin{array}{|c|c|c|c|c|c|c|}\hline&\tiny\text{Strongly Disagree}&\tiny\text{Disagree}&\tiny\text{Mildly Disagree}&\tiny\text{Mildly Agree}&\tiny\text{Agree}&\tiny\text{Strongly Agree}\\\hline\tiny\text{Tumblers: better than pumpers!}^*&&&&&&\checkmark\\\hline\tiny\text{I look fat in this dress.}&\checkmark\\\hline\end{array}$*
Wikipedia gives another style using marked options (by Nicholas Smith):


*Letter codes can also be substituted for numeric options if blanks are to be filled for a list of very many items; e.g., {SD,D,MD,MA,A,SA}. Just don't forget to include the legend!

Reference
Schwarz, N., Knäuper, B., Hippler, H. J., Noelle-Neumann, E., & Clark, L. (1991). Rating scales numeric values may change the meaning of scale labels. Public Opinion Quarterly, 55(4), 570–582.
A: To do analysis with ordinal scales like the Likert you would use nonparametric methods based on ranks.  What matters with ordinal scales is the order if 5 is best, 0 is worst, 1 is better than 0, 2 is better than 1 etc.
Both ratios and intervals are meaningless for ordinal data.  So a scale of 1-6 versus 0-5 doesn't matter and won't affect the analysis.  Starting with 1 is due to tradition rather than necessity.
A: I think the points should be determine as per the framing of questions. Like as, if the questions are related to attitude then points should be given from 1 to 5, not 0 to 4 because we are trying to know the attitude. And attitude can not be lie at 0 level; even respondent mark on the Strongly Disagree option but we can not mention 0 (zero) on this response.
Similar can be other variables.
So, as a researcher we should try to determine the points from 1-5; 1-7 etc.
