How can you find all parameter estimates are statistically significant but without performing any sophisticated calculations?

I have a question that contains a list of parameter estimates and their related standard errors. It then goes on to ask that I explain how I know all parameter estimates are statistically significant at a 5% significance level, but without performing any 'sophisticated calculations'. Does this mean I have to compare the standard errors to the estimators or do I find their t-values?

Normally an exam question like that can be solved by simply calculating the $$t$$-statistics which can be simply done as:
$$t_{\hat{\beta}} = \frac{\hat{\beta}-\beta_0}{se(\hat{\beta})}$$
where $$\hat{\beta}$$ is the estimate, $$\beta_0$$ is the assumed value of beta under null (usually 0) and $$se(\hat{\beta})$$ standard error of the coefficient and then compare it to $$5\%$$ critical value (for large $$n$$ and two sided hypothesis approximately $$1.96$$).
However, you should ask your teacher/supervisor to clarify what is considered 'sophisticated calculation' - some might consider even subtraction and division sophisticated. An approximate rule of thumb that requires even less calculation is to see if the coefficient $$\hat{\beta}$$ (and assuming null hypothesis assumes $$\beta_0=0$$) is twice as large as the standard error.