Chat with AIExam 13: Uncertainty of Numeric Estimates
What is a multichotomous variable?
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VerifiedD
Explain what is a p value, and how it is used in hypothesis testing. Provide an example.
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Answered by Examlex AI CopilotA p-value is a measure of the strength of evidence against the null hypothesis in a hypothesis test. In hypothesis testing, the null hypothesis is a statement that there is no effect or no difference, while the alternative hypothesis is a statement that there is an effect or a difference. The p-value helps us determine whether the evidence from our sample data is strong enough to reject the null hypothesis in favor of the alternative hypothesis.
In hypothesis testing, we calculate the p-value based on the sample data and the assumed null hypothesis. If the p-value is less than a predetermined significance level (usually 0.05), we reject the null hypothesis and conclude that there is enough evidence to support the alternative hypothesis. If the p-value is greater than the significance level, we fail to reject the null hypothesis and conclude that there is not enough evidence to support the alternative hypothesis.
For example, let's say a pharmaceutical company wants to test a new drug to see if it is effective in reducing blood pressure. The null hypothesis would be that the drug has no effect on blood pressure, while the alternative hypothesis would be that the drug does have an effect. After conducting a study, the researchers calculate a p-value of 0.03. Since this p-value is less than the significance level of 0.05, they would reject the null hypothesis and conclude that there is enough evidence to support the alternative hypothesis that the drug does have an effect on blood pressure.
"Statistical uncertainty" means a sample estimate can never be exactly equal to the population parameter.
(31) VerifiedFalse
With the help of an example, illustrate how confidence intervals could be used to assess differences in an outcome variable across values of a categorical independent variable.
(37) How could bias be reduced, if measurement validity has been corrected?
(33) What are the limits, if any, to values of uncertainty measures such as standard error, confidence level, and confidence interval?
(31) A cell in a bivariate correlation matrix shows a value of 1 for the 'R' statistic. How would you interpret this value?
(34) What could be done to minimize faulty inferences made with traditional research methods? Choose the best answer.
(33) Using the paper chosen in question 1, comment on the hypothesis development and testing done by the authors. Would you have done anything differently in this process of hypothesis testing?
(35) A confidence level of 99% is interpreted as the difference between a sample estimate and the population parameter is less than the margin of error 99% of the time.
(38) If the p value of the hypothesis test in Question 13 is calculated to be .003, what conclusion could be made from the test?
(28) Explain what is a 'statistically significant' result from a hypothesis test. Illustrate with an example.
(35) What is a common critique of traditional research methods of testing significance, other than publication bias? Choose the best answer.
(43) Distinguish between interpreting a confidence interval and a compatibility interval.
(33) What is an alternative term used in recent research for "confidence interval"?
(37) What is the statistical measure generally shown in a cross-tabulation between two categorical variables?
(36) What does the value of 'R' represent in a correlation matrix for bivariate data?
(38) In your own words, describe what is 'publication bias'. Provide an example.
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