Tuesday, June 11, 2019

Statistics paper Essay Example | Topics and Well Written Essays - 750 words

Statistics paper - Essay ExampleCommercial try on showed a strong negative correlation (r=0.98) while residential sample showed a strong positive correlation (r=0.97) between the bill coat and the delay. The date of a payment can be predicted by the retroversion equations derived separately for commercial and residential samples.Late bill payments always trouble the service providers by interrupting their future planning and investments. Delay can be varied from a day to few months or sometimes a year. It is really helpful if a service provider can predict the date of the payment.The size of the bill may have a relationship with the number of days the payment delays. It may take a long time for a client to pay a large bill than a small bill or it could be vice versa. However if such a relationship is free-base the service provider can use it to predict payment dates and work accordingly.The mean values of the total and sub samples (commercial and residential) were calculated. Re gression analysis (linear) was performed using outstrip and SPSS statistical packages to find out possible correlations between the size of the bill and number of days the payment delayed. Size of the bill was considered as the independent uncertain in this analysis.Regression analysis for total sample (figure 1) showed no correlation between bill size and delay. However regression analysis for commercial sample (figure 2) showed strong negative correlation. This explains their behavioral trend of paying large bill more quickly than that of the small bills. The residential customers expressed a totally several(predicate) behavior than the commercial customers. They delay the payment as the bill size increases.Amongst the commercial customers the bill size negatively correlated with the delay while it was positively correlated with the delay amongst the residential customers. The date of a payment can be predicted by the following regression

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