When should I use the Paired t-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. Compares numerical data to a known mean. The null hypothesis is that the mean of the data equals the known mean. B. Test the fit of the normal distribution to the data set. C. Test to compare frequency data to a specific population model D. Compare two treatment groups of independent samples where the data meet the assumption that the data fit the normal distribution. E. Compare more than two treatment groups when a normal distribution cannot be met. F. Compare two treatment groups consisting of independent samples with a normal distribution AND unequal variance. G. Compare two treatments consisting of paired data where a normal distribution can be assumed. H. Compare two treatment groups consisting of paired data when the data do not fit the normal distribution. I. Test to see if the frequency data from a population fit a discrete probability distribution. OJ. Compare categorical frequency data with an expected population proportion. No difference between observed and expected proportions is used as the null hypothesis. K. Compare two treatment groups when a normal distribution cannot be assumed. L. More than two treatment groups where a normal distribution can be assumed. M. 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.
When should I use the Paired t-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. Compares numerical data to a known mean. The null hypothesis is that the mean of the data equals the known mean. B. Test the fit of the normal distribution to the data set. C. Test to compare frequency data to a specific population model D. Compare two treatment groups of independent samples where the data meet the assumption that the data fit the normal distribution. E. Compare more than two treatment groups when a normal distribution cannot be met. F. Compare two treatment groups consisting of independent samples with a normal distribution AND unequal variance. G. Compare two treatments consisting of paired data where a normal distribution can be assumed. H. Compare two treatment groups consisting of paired data when the data do not fit the normal distribution. I. Test to see if the frequency data from a population fit a discrete probability distribution. OJ. Compare categorical frequency data with an expected population proportion. No difference between observed and expected proportions is used as the null hypothesis. K. Compare two treatment groups when a normal distribution cannot be assumed. L. More than two treatment groups where a normal distribution can be assumed. M. 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.
A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
Section: Chapter Questions
Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
Related questions
Topic Video
Question
Could you please highlight the correct answer
Transcribed Image Text:When should I use the Paired t-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. Compares numerical data to a known mean. The null hypothesis is that the mean of the data equals the known mean.
B. Test the fit of the normal distribution to the data set.
C. Test to compare frequency data to a specific population model
D. Compare two treatment groups of independent samples where the data meet the assumption that the data fit the normal distribution.
E. Compare more than two treatment groups when a normal distribution cannot be met.
F. Compare two treatment groups consisting of independent samples with a normal distribution AND unequal variance.
G. Compare two treatments consisting of paired data where a normal distribution can be assumed.
H. Compare two treatment groups consisting of paired data when the data do not fit the normal distribution.
I. Test to see if the frequency data from a population fit a discrete probability distribution.
OJ. Compare categorical frequency data with an expected population proportion. No difference between observed and expected proportions is used as the null hypothesis.
K. Compare two treatment groups when a normal distribution cannot be assumed.
L. More than two treatment groups where a normal distribution can be assumed.
M. 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.
Expert Solution
This question has been solved!
Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.
This is a popular solution!
Trending now
This is a popular solution!
Step by step
Solved in 2 steps
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, probability and related others by exploring similar questions and additional content below.Recommended textbooks for you
A First Course in Probability (10th Edition)
Probability
ISBN:
9780134753119
Author:
Sheldon Ross
Publisher:
PEARSON
A First Course in Probability (10th Edition)
Probability
ISBN:
9780134753119
Author:
Sheldon Ross
Publisher:
PEARSON