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When should I use the ANOVA test? Remember that some tests, such as chi squared, can be used under various circumstances. The goal of the test changes based on the situation. Pay attention to the specific conditions noted in parenthesis to ensure you are picking the correct goal. A. Compare two treatment groups when a normal distribution cannot be assumed. B. Compare two treatment groups consisting of independent samples with a normal distribution AND unequal variance. C. Compare two treatment groups of independent samples where the data meet the assumption that the data fit the normal distribution. O D. Test if the median of a data set equals a null hypothesized value when the distribution of the data does not meet the assumption of normalacy. E. Test to compare frequency data to a specific population model F. Compare two treatments consisting of paired data where a normal distribution can be assumed. G. Test to see if the frequency data from a population fit a discrete probability distribution. H. Compares numerical data to a known mean. The null hypothesis is that the mean of the data equals the known mean. I. More than two treatment groups where normal distribution be assumed. J. Compare more than two treatment groups when a normal distribution cannot be met. O K. Test the fit of the normal distribution to the data set. L. Compare categorical frequency data with an expected population proportion. No difference between observed and expected proportions is used as the null hypothesis. M. Compare two treatment groups consisting of paired data when the data do not fit the normal distribution.

When should I use the ANOVA test? Remember that some tests, such as chi squared, can be used under various circumstances. The goal of the test changes based on the situation. Pay attention to the specific conditions noted in parenthesis to ensure you are picking the correct goal. A. Compare two treatment groups when a normal distribution cannot be assumed. B. Compare two treatment groups consisting of independent samples with a normal distribution AND unequal variance. C. Compare two treatment groups of independent samples where the data meet the assumption that the data fit the normal distribution. O D. Test if the median of a data set equals a null hypothesized value when the distribution of the data does not meet the assumption of normalacy. E. Test to compare frequency data to a specific population model F. Compare two treatments consisting of paired data where a normal distribution can be assumed. G. Test to see if the frequency data from a population fit a discrete probability distribution. H. Compares numerical data to a known mean. The null hypothesis is that the mean of the data equals the known mean. I. More than two treatment groups where normal distribution be assumed. J. Compare more than two treatment groups when a normal distribution cannot be met. O K. Test the fit of the normal distribution to the data set. L. Compare categorical frequency data with an expected population proportion. No difference between observed and expected proportions is used as the null hypothesis. M. Compare two treatment groups consisting of paired data when the data do not fit the normal distribution.

Human Heredity: Principles and Issues (MindTap Course List)
Human Heredity: Principles and Issues (MindTap Course List)
11th Edition
ISBN:9781305251052
Author:Michael Cummings
Publisher:Michael Cummings
Chapter3: Transmission Of Genes From Generation To Generation
Section3.7: Mendelian Inheritance In Humans
Problem 2EG: For most cases, a p value of 0.05 is used to determine whether results fit expected values. Is this...
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When should I use the ANOVA test? Remember that some tests, such as chi squared, can be used under various circumstances. The goal of the test changes based on the situation. Pay attention to the specific conditions noted in parenthesis to ensure you are picking the correct goal. A. Compare two treatment groups when a normal distribution cannot be assumed. B. Compare two treatment groups consisting of independent samples with a normal distribution AND unequal variance. C. Compare two treatment groups of independent samples where the data meet the assumption that the data fit the normal distribution. O D. Test if the median of a data set equals a null hypothesized value when the distribution of the data does not meet the assumption of normalacy. E. Test to compare frequency data to a specific population model F. Compare two treatments consisting of paired data where a normal distribution can be assumed. G. Test to see if the frequency data from a population fit a discrete probability distribution. H. Compares numerical data to a known mean. The null hypothesis is that the mean of the data equals the known mean. I. More than two treatment groups where normal distribution be assumed. J. Compare more than two treatment groups when a normal distribution cannot be met. O K. Test the fit of the normal distribution to the data set. L. Compare categorical frequency data with an expected population proportion. No difference between observed and expected proportions is used as the null hypothesis. M. Compare two treatment groups consisting of paired data when the data do not fit the normal distribution.
Transcribed Image Text:When should I use the ANOVA test? Remember that some tests, such as chi squared, can be used under various circumstances. The goal of the test changes based on the situation. Pay attention to the specific conditions noted in parenthesis to ensure you are picking the correct goal. A. Compare two treatment groups when a normal distribution cannot be assumed. B. Compare two treatment groups consisting of independent samples with a normal distribution AND unequal variance. C. Compare two treatment groups of independent samples where the data meet the assumption that the data fit the normal distribution. O D. Test if the median of a data set equals a null hypothesized value when the distribution of the data does not meet the assumption of normalacy. E. Test to compare frequency data to a specific population model F. Compare two treatments consisting of paired data where a normal distribution can be assumed. G. Test to see if the frequency data from a population fit a discrete probability distribution. H. Compares numerical data to a known mean. The null hypothesis is that the mean of the data equals the known mean. I. More than two treatment groups where normal distribution be assumed. J. Compare more than two treatment groups when a normal distribution cannot be met. O K. Test the fit of the normal distribution to the data set. L. Compare categorical frequency data with an expected population proportion. No difference between observed and expected proportions is used as the null hypothesis. M. Compare two treatment groups consisting of paired data when the data do not fit the normal distribution.
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