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BUAN 6312 Exam 2 Questions and Answers Graded A+

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BUAN 6312 Exam 2 Questions and Answers Graded A+ Question: What is the purpose of hypothesis testing in statistical analysis? Answer: Hypothesis testing is used to determine if there is enough statistical evidence to support a specific hypothesis about a population parameter. It helps in m...

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  • August 13, 2024
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  • BUAN 6312
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BUAN 6312 Exam 2 Questions and
Answers Graded A+
Question: What is the purpose of hypothesis testing in statistical analysis?


Answer: ✔✔ Hypothesis testing is used to determine if there is enough statistical evidence to

support a specific hypothesis about a population parameter. It helps in making inferences or

decisions based on sample data.




Question: What are Type I and Type II errors in hypothesis testing?


Answer: ✔✔ A Type I error occurs when a true null hypothesis is incorrectly rejected, while a

Type II error occurs when a false null hypothesis is not rejected. Type I error is also known as a

false positive, and Type II error is known as a false negative.




Question: What does a p-value represent in hypothesis testing?


Answer: ✔✔ The p-value represents the probability of obtaining test results at least as extreme

as the observed results, assuming that the null hypothesis is true. A low p-value indicates strong

evidence against the null hypothesis.




Question: How is a confidence interval different from a hypothesis test?




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, Answer: ✔✔ A confidence interval provides a range of values within which a population

parameter is expected to fall, with a certain level of confidence. In contrast, a hypothesis test

assesses whether there is sufficient evidence to reject a null hypothesis about the parameter.




Question: What is the role of the significance level (alpha) in hypothesis testing?


Answer: ✔✔ The significance level (alpha) is the threshold used to determine whether the p-

value indicates sufficient evidence to reject the null hypothesis. Common values for alpha are

0.05, 0.01, and 0.10.




Question: How do you interpret the results of a t-test?


Answer: ✔✔ The results of a t-test are interpreted by comparing the calculated t-value to the

critical t-value from the t-distribution table, based on the significance level and degrees of

freedom. If the calculated t-value exceeds the critical value, the null hypothesis is rejected.




Question: What is the difference between a one-sample t-test and a two-sample t-test?


Answer: ✔✔ A one-sample t-test compares the mean of a single sample to a known value or

population mean, while a two-sample t-test compares the means of two independent samples to

determine if there is a significant difference between them.




Question: What is an ANOVA test used for?

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