Results OI Other PD VD Row Totals 2014 258 (240.56) [1.26] 8 (3.17) [7.34] 764 (
ID: 3438367 • Letter: R
Question
Results
OI Other PD VD Row Totals
2014 258 (240.56) [1.26] 8 (3.17) [7.34] 764 (791.50) [0.96] 234 (228.77) [0.12] 1264
2013 243 (236.18) [0.20] 4 (3.12) [0.25] 783 (777.10) [0.04] 211 (224.60) [0.82] 1241
2012 226 (218.86) [0.23] 2 (2.89) [0.27] 722 (720.12) [0.00] 200 (208.13) [0.32] 1150
2011 178 (181.56) [0.07] 0 (2.40) [2.40] 593 (597.38) [0.03] 183 (172.66) [0.62] 954
2010 156 (183.84) [4.22] 0 (2.43) [2.43] 629 (604.90) [0.96] 181 (174.83) [0.22] 966
Column Totals 1061 14 3491 1009 5575 (Grand Total)
The chi-square statistic is 22.7594. The P-Value is 0.02984. The result is significant at p < 0.05.
I performed this chi-square contingency test, and have been asked how I statistically determined that (PD) is the leading reason behind most incursions, with operational incidents (OI) being second, with vehicle/pedestrian (V/PD) coming in third, and other factors in fourth place.” How did you statistically determine this?
I am stuck, other than saying that the observed and expected values are higher or lower than other categories how do I explain or determine this statistically based off of the table?
Thanks.
Explanation / Answer
To determine the effect of each variable on the most number of incursions, we would ideally use the regression method. Here you have found that there is correlation between the variables. Then perform regression analysis to answer the second part of the question.
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