Explain in full the background of the study, the research problem, and the research question. 

Also, Explain fully the meaning of Alpha, Null Hypothesis, Alternative Hypothesis, and Methodology. Finally, summarize the results, which are provided below, and include them in the conclusion.

Explain fully the: 

Background of the Study: Based on various reports, the conventional wisdom is that the number of drug-related overdose fatalities in the fifty United States and the District of Columbia (D.C.) has been increasing in recent years. In recent years, the Centers for Disease Control has compiled the raw numbers of overdose-related deaths in the fifty United States and the District of Columbia (D.C.). However, there are no statistical analyses of these numbers (e.g., t-tests, z-tests, Anova single factor, etc. The information was obtained from https://www.cdc.gov/drugoverdose/deaths/index.html.

Research Problem: In recent years, there has been a lack of statistically oriented tests and research regarding the truth or falsity of increased drug-related overdose fatalities in the fifty United States and the District of Columbia (D.C.).

Research Question: Have drug-related overdose fatalities increased in the 50 United States and the District of Columbia since the turn of the 21st century?

 

Explain fully the meaning of: 

Alpha: 

Null Hypothesis: 

Alternative Hypothesis:

Methodology: 

 

Explain the results as they were presented in the professor's study below. In addition, summarize the results of the prior paragraphs. That includes the results below.

 

Results - 

 

Anova Single Factor, based on the O.D. stats for 2014, 2016, and 2020, is based on the raw data (Table Twelve). The data was normalized through the Log10 procedure to "cure" problems with the kurtosis, which could disrupt the accuracy of a statistical test. The Null Hypothesis based on an alpha of 0.05 was rejected; some or all of the groups show significant statistical differences F(3.69) > F crit(3.05), a reliable indication that something of statistical difference is occurring; the p-value is 0.02, less than 0.05, an indication that at least some of the three means are dissimilar and, therefore, significant.

 

As per statistical rules, t-tests, two samples for means assuming equal variances were conducted on all groups. However, an ANOVA single factor for three data sets requires some adjustment in the alpha levels; this is accomplished as follows:0.05/3 = 0.0167The alpha value for the t-test is now 0.0167; if the p-value for the t-tests is less than .0167, it will indicate a significant result; if the p-value is > 0.167, the results are not significant. The t-tests indicated that there was no statistical difference between the stats for 2014-2016 (p = The t-tests indicated that there was a statistical difference between the stats for 2014-2020 (p = 0.007); this is a highly significant effect and shows a difference in the O.D. stats.0.25); this is > 0.0167. The t-tests indicated no statistical difference between the stats for 2016 -2020 (p = 0.125); this is > 0.0167. More testing is required, but the likelihood is that there are marked increases in the statistics, such that there may not be a difference between the tests in this period of upside