Tuesday, September 10, 2019

Cause and Effect and Correlation Essay Example | Topics and Well Written Essays - 250 words

Cause and Effect and Correlation - Essay Example An article published by the John Hopkins University (2000) indicated that â€Å"predominantly black, low-income neighborhoods in Baltimore were eight times more likely to have carry-out liquor stores than white or racially integrated neighborhoods† (John Hopkins University, 2000, p. 1). Bradtmiller cited Interim Chief of the IU Police Department Jerry Minger as stating that â€Å"There are so many factors that are involved in violence,† Minger said. â€Å"It could be something like a domestic problem or a hate crime and have not anything to do with alcohol† (Bradtmiller, 2010, p. 1). Again, one agrees that the abundance of liquor stores is a contributory factor to criminal activities. In higher crime areas, there are usually more police; does that mean that police cause crime? This statement is totally unfounded, unsubstantiated and does not indicate any correlation to criminal activities. The reason why police presence is needed is to specifically address the crimes committed in high crime areas. There could be a correlation that when there are high incidents of crime, there would necessarily be greater number of police to address the criminal activities in the area. To determine a reliable correlation between the number of liquor stores and the number of crimes in low income neighborhoods, what kind of experiment might you design? A correlation analysis between two variables (number of liquor stores and number of crimes) would determine a reliable correlation between the two. What kind of correlation number would make you feel fairly certain that there is a solid connection between larger numbers of liquor stores in low income neighborhoods and resulting crime? The correlation number ‘r’ (Pearson r) would establish whether there is a solid connection between the two variables. As revealed in Knowledge Base (2006), â€Å"r will always be between -1.0 and +1.0. if the correlation is negative, we have a negative relationship; if its positive,

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