Final answer:
To find z-scores corresponding to different confidence levels, one can use a calculator with statistical functions or a z-table. These values help in constructing confidence intervals and conducting hypothesis tests for significance.
Step-by-step explanation:
The student's question seems to revolve around the concept of finding z-scores for different confidence levels and interpreting p-values with respect to a given significance level in a statistical context.
To calculate these values accurately, one can use statistical tools like a TI-83, 83+, or 84+ calculator, appropriate software, or a z-table.
For example, to find z0.05, which corresponds to a 95% confidence level (where the area to the left is 0.95 and the area to the right is 0.05), you can use the calculator command invNorm(0.95,0,1) which would return a z-score of 1.645. To find z0.01 for a 99% confidence level (where the area to the right of z0.01 is 0.01), you would similarly use invNorm(0.99,0,1) or look up in the z-table to obtain a z-score of about 2.326.
For interpreting p-values at a significance level of α = 0.05, if a calculated p-value is lower than 0.05, the null hypothesis is typically rejected, indicating statistically significant results.
For example, using the 2-PropZTest will provide a p-value that can be compared to α to help make decisions regarding statistical tests.