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Updated: May 23, 2026
07:25
Driving Under the Influence: How Music Listening Affects Driving Behaviors
Published on: March 27, 2019
Utah's Move From 0.08 to 0.05 Blood Alcohol Concentration Per Se Policy: Effects on Driver Crash Fatalities Compared
Kaigang Li1, James C Fell2, Niyousha Hosseinichimeh3
1Department of Health and Exercise Science, Colorado State University, Fort Collins, Colorado; Colorado School of Public Health, Fort Collins, Colorado.
American Journal of Preventive Medicine
|May 21, 2026
Summary
This article has been temporarily removed due to an unspecified reason. A replacement or reinstatement will be provided soon, with details on the withdrawal policy available.
Area of Science:
- Scientific publishing ethics
- Article integrity and retraction
Background:
- Concerns regarding the accuracy and validity of published scientific research.
- The importance of transparent processes for article withdrawal and reinstatement.
Purpose of the Study:
- To inform readers about the temporary removal of this specific article.
- To provide information on the publisher's policy regarding article withdrawals.
Main Methods:
- Article withdrawal process.
- Publisher's policy on article retraction and reinstatement.
Main Results:
- The article in question has been temporarily removed from publication.
- A forthcoming replacement or reinstatement will clarify the situation.
Conclusions:
- The publisher is committed to maintaining the integrity of scientific literature.
- Readers are directed to the official policy for detailed information on article withdrawal procedures.
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The test of independence is a chi-square-based test used to determine whether two variables or factors are independent or dependent. This hypothesis test is used to examine the independence of the variables. One can construct two qualitative survey questions or experiments based on the variables in a contingency table. The goal is to see if the two variables are unrelated (independent) or related (dependent). The null and alternative hypotheses for this test are:
H0: The two variables (factors)...
H0: The two variables (factors)...
01:08Determination of Expected Frequency
Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...
01:21Introduction to Test of Independence
In statistics, the term independence means that one can directly obtain the probability of any event involving both variables by multiplying their individual probabilities. Tests of independence are chi-square tests involving the use of a contingency table of observed (data) values.
The test statistic for a test of independence is similar to that of a goodness-of-fit test:
The test statistic for a test of independence is similar to that of a goodness-of-fit test:
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