Statistics for Data Science and Business Analysis - Establishing a Rejection Region and a Significance Level

The video tutorial explains hypothesis testing, focusing on the significance level, hypothesis testing mechanics, and both two-tailed and one-sided tests. It covers the importance of selecting an appropriate significance level based on context and provides examples to illustrate the concepts. The tutorial also details the process of hypothesis testing, including calculating the Z score and determining rejection regions.

What is the significance level in hypothesis testing?

• The probability of accepting a true null hypothesis

• The probability of accepting a false null hypothesis

• The probability of rejecting a false null hypothesis

• The probability of rejecting a true null hypothesis

In which scenario would you choose a lower significance level?

• When analyzing company performance

• When predicting consumer behavior

• When testing machine accuracy

• When testing human behavior

What is the null hypothesis in hypothesis testing?

• A statement that the sample mean is greater than the population mean

• A statement that the sample mean is less than the population mean

• A statement that the sample mean is equal to the population mean

• A statement that the sample mean is different from the population mean

How is the Z-score calculated in hypothesis testing?

• Sample mean divided by standard error

• Sample mean minus hypothesized mean divided by standard error

• Hypothesized mean divided by sample mean

• Standard error divided by sample mean

What does a Z-score close to zero indicate?

• The null hypothesis should be rejected

• The null hypothesis should be accepted

• The alternative hypothesis is true

• The sample mean is far from the hypothesized mean

In a one-sided test, where is the rejection region located?

• On both sides

• In the middle

• On the left or right side

• There is no rejection region

What is the Z-score cutoff for a one-sided test with a significance level of 0.05?

• 1.96

• 0.05

• 1.645

• 2.33