R Programming for Statistics and Data Science - Hypothesis Testing

The video tutorial covers the topic of hypothesis testing, explaining the six steps in data-driven decision making. It introduces the concept of a hypothesis, differentiating between alternative and null hypotheses, and provides examples to illustrate these concepts. The process of hypothesis testing is detailed, including the importance of the null hypothesis and the inability to prove the alternative hypothesis. The tutorial also explains the ingredients of hypothesis testing, such as the rejection region and significance level, and discusses the differences between two-tailed and one-tailed tests.

What is the first step in data-driven decision making?

• Generate a theory

• Formulate a hypothesis

• Define a research question

• Execute the test

Which of the following is a testable hypothesis?

• Apples are a popular fruit

• Apples in New York cost more than $1.75 per pound

• Apples in New York are expensive

• New York has many apple orchards

What does the null hypothesis (H0) represent?

• A hypothesis that cannot be tested

• A hypothesis that is always accepted

• The hypothesis that the theory is false

• The hypothesis that the theory is true

In a one-tailed test, what is the null hypothesis?

• The population mean is equal to a specific value

• The population mean is greater than a specific value

• The population mean is not equal to a specific value

• The population mean is less than or equal to a specific value

What is the significance level (alpha) in hypothesis testing?

• The probability of making a Type I error

• The probability of proving the alternative hypothesis

• The probability of rejecting the null hypothesis if it is true

• The probability of accepting the null hypothesis

What does a two-tailed test assess?

• Whether the population mean is greater than a specific value

• Whether the population mean is less than a specific value

• Whether the population mean is equal to a specific value

• Whether the population mean is different from a specific value

What is the rejection region in hypothesis testing?

• The range of values where the alternative hypothesis is rejected

• The range of values where the alternative hypothesis is accepted

• The range of values where the null hypothesis is rejected

• The range of values where the null hypothesis is accepted