Statistical analysis of choosing between four different versions

[jedidrengen]

Hi all,
I am making a google survey that will help me figure out what landing page my users like the best. They have four different options A, B, C and D. I have 14 respondents and ALL chose B. My population is so small, so what can I conclude statistically?

I have written "Since there are only 14 respondents, the population is too small to make a proper statistical analysis that will enable us to either accept or reject the hypotheses with a 95% confidence interval. The results points in a very specific direction though, so we feel confident to choose landing page B."
- Is this correct?

Link to survey: https://docs.google.com/forms/d/e/1...QSJ51s2y4myI-0ewMFTmZOsQ/viewform?usp=sf_link

What statistical analysis should I use in this scenario and do any of you have a good online calculator that will help me?

Hope you can help

Happy thoughts,
Simon

 

[Karabiner]

Since you confuse basic concepts like sample and population , and the rest of your statement
is gibberish (I don't mean to be rude here, just realistic) , why do you not just resort
to common sense? "I made a small experiment with 14 participants, and all of them chose B"
with the conclusion: "I guess that this supports the idea that B ist preferred by most, but to
be sure, we need more data." By the way, you did not mention whether the 14 participants
were typical users. Maybe sampling was biased.

With kind regards

Karabiner

 

[jedidrengen]

Hi Karabiner,
Thank you for your reply, and sorry about exposing you to my gibberish. I am a noob, I know Very good idea to keep it basic with common sense. I talked about the users earlier in my description, not here in this forum.

If I later decide to make a survey that gives me more varied preferences, do you know of an online tool that will help me calculate e.g. standard deviation? What is the statistical method called I need to use?

 

[Dason]

One thing I would advise to keep in mind in the future is to think about the analysis you would want to perform on the days before you even do your data collection/sampling. You initial post essentially says you took a sample, got the strongest possible result, and still you didn't think it was strong enough. At that point you have to question what the point of the exercise was in the first place.