This article discusses What Impact do different legal approaches have on people who drink in the US.
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What Impact do different legal approaches have on people who drink in the US?
Drunk driving defines the process where an individual controls a moving motor while intoxicated. Most US citizens are not aware of the impacts of drunk driving and drinking and driving laws. The National Highway Traffic Safety Administration conducts educational programs regarding traffic rules towards discouraging driving under the influence of alcohol.
In 2009, the institution recorded approximately 11 000 annual deaths caused by drunk driving, attracting legal sanctions against culprits and necessitating improvement of traffic safety conditions. For this reason, this research study seeks to establish the impacts of different legal approaches on people who drink and drive in the US.
The t-test was chosen as the preferred inferential statistic to test hypotheses in establishing means. The reason for selecting the t-test is because it allows a researcher to scale down collected data to one number. With the study exhibiting only one variable, the number of people who drink and drive in the US, the researcher can draw an assumption of dependent variables fitting a normal distribution.
The dependent variable allows for a given probability of outcome to be established before data on the number of drunk divers is collected. The formula for a one-sample t-test for a population with specified theoretical mean is given as:
For a given set of values representative of the number of people who drink and drive in the US, X, µ is the theoretical mean, m is the actual mean, s is the standard deviation while n the sample size. Hypothesis testing provides mutual relations of a population as being either null or alternate. The null hypothesis shows no effect of data on a given population, while the alternate hypothesis depicts the presence of an effect. The most common errors conducting a t-test are Type I and Type II errors arising from wrong findings on the null hypothesis.
This research will utilize a sample size of 50 individuals. Decade-long records show that more middle-aged adults and youths make up most culprits involved in drunk driving. Therefore, the study will target middle-aged men and women together with young adults and randomly pulled over a specific highway. With this selection technique, it will be possible to make assumptions and possibly accurate trends from records. Despite the many vehicles plying the highway, police checks will allow the researcher to sample drivers and collect needed information for the study. Selection will be on a random basis.
The research study is based on the impacts of different legal approaches on people who drink while driving in the US. From this research question, there is only one identifiable variable: the number of people who drink and drive in the US. A measure of this variable is done through counts and solved through an equation in a ratio format. This measurement scale provides a definite calculation of different data sets as ratios with identifiable ‘true zero.’ The capability of ratios to combine concepts of nominal, ordinal, and interval scales gives reliable results.
Additionally, the nature of the research variable is categorical. The values drawn from categorical variables are qualitative since they describe and answer the question, ‘what type’ and ‘which category.’ For this reason, categorical variables can be referred to as qualitative variables, also because their representation is not numeric. The variable is measured through observations that can either be organized in a logical sequence or not.
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The t-test is an inferential statistic considered for this research for its compelling nature of establishing distinctive relations with means of data. When comparing different data, a researcher can draw contrasting measurement scales between the t-value and critical value of the data table. This choice of a t-test is based on the number of people drinking and driving in the US, exhibiting different characteristics in terms of gender, age, social class. Research results might show significant disparities depending on the t-value and probability of the sample.
A t-test will provide myriad results that can exhibit discrepancies, not unless multiple repeats are done. The values of the number of people drinking while driving in the US is measured against possible impacts of the different implications of legal approaches. With the value established from the set of data variables, the researcher ascertains whether the results are within acceptable probability levels.
Since t-tests range from one type to the other, biases and assumptions are drawn from conclusions and results. Also, the values providing different variable results allow the researcher to establish the final results’ quality. This study will utilize the one-sample t-test, which has four assumptions. The first assumption is that dependent variables closely have a normal distribution. Secondly, the dependent variables are devoid of outliers. Additionally, observations are independent of one another, and lastly, a dependent must be continuous.
In any case, the magnitude of effect should be too small or too large to address the research topic. This exemplifies the practical significance of the research question hence the ability to draw relevant conclusions. Therefore, the t-test is best suited for this study in answering the research question; what impact do different legal approaches have on people who drink and drive in the US?
De Winter, J. C. (2013). Using the Student’s t-test with extremely small sample sizes. Practical Assessment, Research, and Evaluation, 18(1), 10.
Fox, J., Friendly, M., & Weisberg, S. (2013). Hypothesis tests for multivariate linear models using the car package. The R Journal, 5(1), 39-52.
Xu, M., Fralick, D., Zheng, J. Z., Wang, B., Tu, X. M., & Feng, C. (2017). The differences and similarities between two-sample t-test and paired t-test. Shanghai archives of psychiatry, 29(3), 184.