R Programming for Statistics and Data Science - Test for the Mean - Population Variance Known

The video tutorial covers hypothesis testing, focusing on tests for a single mean with known variance. It uses data scientist salary data from Glassdoor to illustrate the process. The tutorial explains setting up null and alternative hypotheses, standardizing variables, and creating a Z test function in R. It also discusses decision rules and significance levels, demonstrating how to determine if the mean salary is statistically different from a given value.

What does a Z score of -4.67 indicate in the hypothesis testing example?

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How is the critical value determined for a two-sided test at a 5% significance level?

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What conclusion can be drawn if the Z score is higher than the critical value?

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