I need help with this using the calculator:

"Example 8.1:A common measure of intelligence is the intelligence quotient (IQ) test (Castles, 2012; Naglieri, 2015; Spinks et al., 2007) in which scores in the general healthy population are approximately normally distributed with 100 15 ( ). Suppose we select a sample of 100 graduate students to identify if the IQ of those students is significantly different from that of the general healthy adult population. In this sample, we record a sample mean equal to 103 (M = 103). Compute the one-sample z test to decide whether to retain or reject the null hypothesis at a .05 level of significance ( = .05)." (Privitera 3rd Edition, page 250, Example 8.1)

calculator:

https://mathcracker.com/z-test-for-one-mean

1. What was the z-test statistic?
2. Was it significant and how do we know?
3. Using Cohen's d-test to judge the effect size, calculate the value of Cohen's d and interpret the outcome. Is the effect size small, medium, or large?
4. Extending your knowledge: our sample size of 100 is fairly large. At what smaller sample size does the difference between the population mean of 100 and the sample mean of 103 become NOT statistically significant? Keep reducing the sample size in the calculator until you find out. Post that sample size here when you discover it. Explain how this does or does not change your thinking about the impact of sample size on significance testing.
5. Extending your knowledge: What is the difference between a z-score, and a z-test?