Exploring Null and Alternative Hypotheses in Hypothesis Testing

This video provides an introduction to hypothesis testing, focusing on how to state null and alternative hypotheses. It includes four examples: calculator mass, high school completion rates, student GPA, and vehicle ownership. Each example demonstrates how to identify the null and alternative hypotheses based on the context, whether dealing with means or proportions.

What does the null hypothesis typically represent in hypothesis testing?

• An untestable scientific claim

• A disproven scientific theory

• The status quo or currently accepted value

• A new theory proposed by a researcher

What symbol is used to represent the alternative hypothesis?

• H_0

• H_p

• H_a

• H_m

In the context of hypothesis testing, what does the mean symbol 'mu' represent?

• Average value

• Percentage

• Proportion

• Difference in values

What statistical measure is used when dealing with the word 'average' in hypothesis testing?

• Median

• Mean

• Proportion

• Percentage

If a teacher believes the average GPA is different from 2.7, what is the null hypothesis?

• The mean GPA is more than 2.7

• The mean GPA is less than 2.7

• The mean GPA is not 2.7

• The mean GPA is 2.7

What would be the alternative hypothesis if a student believes less than 80% of their peers will complete high school?

• p >= 0.80

• p < 0.80

• p = 0.80

• p > 0.80

What does the proportion p < 0.80 indicate in hypothesis testing?

• More than 80% completion rate

• Exactly 80% completion rate

• Less than 80% completion rate

• At least 80% completion rate

If the accepted value is that no more than 75% of residents own a vehicle, what would the null hypothesis be?

• p >= 0.75

• p <= 0.75

• p > 0.75

• p = 0.75

What is the alternative hypothesis if a researcher believes more than 75% of residents own a vehicle?

• p >= 0.75

• p > 0.75

• p = 0.75

• p <= 0.75

In hypothesis testing, what does disproving the null hypothesis imply about the alternative hypothesis?

• It is likely incorrect

• It is proven without doubt

• It is likely correct

• It has no impact