Evaluating Website Changes Through Hypothesis Testing and Significance Levels

The video tutorial explains hypothesis testing using a website color change example. It covers setting up null and alternative hypotheses, determining significance levels, collecting sample data, calculating p-values, and making decisions based on statistical evidence. The tutorial emphasizes understanding the probability of sample statistics under the null hypothesis and deciding whether to reject it based on the p-value.

What was the initial mean time users spent on the website before any changes?

• 30 minutes

• 20 minutes

• 25 minutes

• 15 minutes

What is the purpose of setting up a null hypothesis?

• To calculate the exact mean time

• To predict future outcomes

• To prove the change is effective

• To assume no effect from the change

What does the alternative hypothesis suggest in this scenario?

• The mean time is less than 20 minutes

• The mean time is greater than 20 minutes

• The mean time is exactly 20 minutes

• The mean time is unpredictable

What is the significance level denoted by?

• Alpha

• Delta

• Gamma

• Beta

What significance level was chosen for this test?

• 0.10

• 0.15

• 0.05

• 0.01

What sample size was used to test the new website background?

• 50

• 75

• 150

• 100

What does a p-value represent in hypothesis testing?

• The probability of the sample mean being exactly 20 minutes

• The probability of observing the sample data given the null hypothesis is true

• The probability of the null hypothesis being true

• The probability of the alternative hypothesis being true

If the p-value is less than the significance level, what decision is made?

• Reject the null hypothesis

• Accept the null hypothesis

• Accept the alternative hypothesis

• Do nothing

What was the p-value calculated in the example that led to rejecting the null hypothesis?

• 0.03

• 0.05

• 0.07

• 0.01

What is a common misconception about the p-value?

• It measures the probability of the sample mean being exactly 25 minutes

• It measures the probability of the null hypothesis being true

• It measures the probability of the sample data

• It measures the probability of the alternative hypothesis being true