Fisher test: odds ratio greater than 1 and p-value greater than 0.05 Is it possible that in the output of fisher.test() in R p-value is grater than 0.05 and odds ratio is not equal to 1?

I have this table.
The output of fisher.test() is:

P-value=0.1789 indicates no association between response and lubricant.
OR=2.7 indicates differences for lubricant=0 and lubricant=1
Is this possible?
isn't that contradictory?
Thank you!
 A: It just means that the observed odds ratio is not dramatic enough to convince you, at the $0.05$-level, that the null hypothesis is false. Sometimes this happens. In fact, one of the reasons hypothesis testing is valuable is because it makes us do more than just observe something and draw conclusions. Yes, it is inarguable that you have different odds in your sample, but that is not enough to make you think the null hypothesis of equal odds is wrong.
The statistical theory of hypothesis testing gives a relationship between hypothesis tests and confidence intervals, and when you look at your confidence interval, you see it ranging from $0.56$ to $14.7$. Loosely speaking, this means that any odds ratio in that range is plausible, so there is no evidence against an odds ratio of $1$.
For a simple example, imagine flipping a coin four times and getting $HTHH$. You wonder if the coin is fair, yet you observed $75\%$ of the flips landing on $H$. Is that enough to convince you that the coin is unfair? What about if you flipped the coin a thousand times and got $75\%$ of the flips to be $H$? Would that convince you the coin is unfair? (What if $75\%$ of a billion or a trillion flips landed on $H$?)
