# confidence intervals 95% we do z = qnorm( 0.95) or z = qnorm( 0.975) [duplicate]

I want to know for sure when we compute the 95% confidence interval for mean/prop, we get z = qnorm(0.95) or z = qnorm(0.975)?

As I understand it, you want to know when to use a certain quantile (qnorm). This will depend on the level of significance set for your test. For example, consider a hypothesis test on which you want to test, $$H_0: \mu = \mu_0 \: \times \: \mu \neq \mu_0$$. It is known that $$Z_{test} = \frac {X- \mu_0}{\sigma} \sim N(0,1)$$ As it is a bilateral test (see the hypotheses), the level of significance set is associated with the quantile of your test statistic ($$Z_ {test}$$). For, $$\alpha = 1- \lambda/2$$, because the test is bilateral ($$\alpha$$ being the level of significance and $$\lambda$$ being the associated trust).
If you set a significance level of say $$\alpha = 0.05$$ you will have the equivalent quantile will be the $$\lambda = 1-\alpha/2 = 0.975$$ quantile of an $$N(0.1)$$, that is, $$qnorm(.975) \approx 1.959964$$, if $$\alpha = 0.1$$ the quantile will be $$qnorm(.95) \approx 1.644854$$.