Wednesday, December 18, 2019

Unemployment Rate Statistical Summary and Analysis

Unemployment Rate Statistical Summary Analysis Month Rate Jan. (2009) 7.6 Feb. 8.1 Mar. 8.5 Summary Analysis Apr. 8.9 Mean: 9.1 May 9.4   Jun. 9.5 Std. Deviation: 0.645943128 Jul. 9.4   Aug. 9.7 Sep. 9.8 Oct. 10.2 Nov. 10.0 Dec. 10.0 Jan. (2010) 9.7 Feb. 9.7 Mar. 9.7 Apr. 9.9 May 9.7 Jun. 9.5 Jul. 9.5 Aug. 9.6 Sep. 9.6 Oct. 9.6 Nov. 9.8 Dec. 9.4 Jan. (2011) 9.0 Feb. 8.9 Mar. 8.8 Apr. 9.0 May 9.1 Jun. 9.2 Jul. 9.1 Aug. 9.1 Sep. 9.1 Oct. 9.0 Nov. 8.6 Dec. 8.5 Jan. (2012) 8.3 Feb. 8.3 Mar. 8.2 Apr. 8.1 May 8.2 Jun. 8.2 Jul. 8.3 Unemployment and the Expansion Decision A business faced with a perceived demand for its product but the continuing uncertainty of the current economic situation would want to examine a variety of current statistics and determine the probability of such indicators improving or worsening the prospects for their business (Weiers, 2010; Johnson Bhattacharyya, 2010). The unemployment rate is one key statistic for many businesses to consider, as it affects both the companys employment figures and costs and its ability to sell products to consumers (Weiers, 2010). In order to determine if expansion is advisable to meet perceived demand at a time of economic uncertainty, a cursory analysis of unemployment rates and an application of some basic principles of statistics and probability might form the beginnings of a larger and more detailedShow MoreRelatedAnalysis Of The American Community Survey1580 Words   |  7 Pagesvariable of personal income is influenced by seven explanatory variabl es; college education, population, unemployment rate, poverty rate and race (share_white, share_black and share_hispanic). In this study, the data analysis has showed a statistical significance on personal income affected by poverty rate and college education of the police victims. The analysis shows population, unemployment rate and race as inconclusive. 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