Economic Data Analysis

CRIME CLEARANCE RATE (a ) convention Linear ModelThe General Linear Model is of the formWhere : Yt dependent variable ?o y-intercept ?1 and ?2 are the partial regression coefficients for the independent variables X1t and X2t and ?t is the error term for observation ( cadence ) t . This equation cannister be extended to several independent variables . Non- additive equations such as the production function as applied to crime clear-up browse preceding(prenominal) , can be reduced to a linear form by logarithmic (common or natural logarithms ) teddy . For this exercise , the general linear model after entropy transformation by natural logarithm is : lnCR 3 .32 -0 .26t 0 .37 lnF 0 .45 lnX1 0 .84 lnX2 . The variable t has a interdict coefficient indicating a decreasing trend of clearance rate through and through mStatistical softwares like SAS , SPSS , and Minitab has procedures (e .g PROC GLM ) for computing the Generalized Linear Model for analytic thinking of Variance (ANOVA ) for experimental designs and regression analysis . This procedure allows the exploiter to specify the dependent and independent variablesTest for assumptions of no serial correlativity - by Durbin-Watson probe applicable only to first auto regressive systems (BoydOne of the assumptions of the general linear model is that the s are on an individual basis distributed with mean zero and variance ?2 . For a time seriesViolation of this assumption leads to autocorrelation , and that the error term at time i has an effect on the error term of another time j (BoydThe testNull theory Ho 0Alternative hypothesis :Ha ? 0is (PowellThere is a table for the critical values for DW tests . There three finale regions : accept null hypothesis reject the null hypothesis indecision when the test can neither be jilted or not rejected (Boydwould reject Ho if DW 2 (1- z ?N , where z ) is the upper standard convention critical value for a size of it ?

test (PowellThe equations derived above have DW s closer to 2 (no serial correlation : For the car-theft entropy (1974-2001 ) DW 2 .12 1974-1987 , DW 2 .01 and for 1988-2001 , DW 1 .92Test for normalityThe Shapiro-Wilk (1965 ) test is used to test if data is normally distributed . The Wilks Shapiro test statistic (Heckert , 2003 ) is defined as is the ideal mean of the data , and w (w1 , w2 , wn ) or M denotes the evaluate values of standard normal statistics for a audition of size n and V is the corresponding covariance matrixW may be model of as the squared correlation coefficient between the ed sample values (X ) and the wi . The wi are approximately proportional to the normal hit Mi . W is a measure of the straightness of the normal probability plot , and small values indicate departures from normalityMany statistical softwares include procedures for testing normalityDataplot statistical software has PPCC PLOT overtop based on a similar concept describe above . Its syntax isWILKS SHAPIRO NORMALITY TESTwhere is the response variable creation tested and where the is optionalDataplot uses Algorithm AS R94 (SWILK sub routine...If you want to travel a full essay, order it on our website: Ordercustompaper.com

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