Confidence intervals and one-wayd hypotheses for correlations
I have two questions:
1) When I do Bayesian tests for correlations and get a confidence interval in JASP - is that a confidence interval for the effect size or for the correlation?
2) When changing my hypothesis to be one-way (in a certain direction), the confidence interval also changes. Would it, for this reason, be better to do a two-way test instead, so that I get a confidence interval that better represents what the confidence interval looks like in the population? Like, even if I expect the correlation to go in a certain direction, wouldn't the confidence interval for the non-directed hypothesis give me the best approximation of what the effect actually looks like "in the population"? Like, should the outcome really change based on if my expectation change? I mean, my expectation could be terrible...