Dear Team,   I work for a logistic & supply chain client. I am trying to run a linear regression model on freight as the dependent var and there are like 8-9 independent variables which add up to the total freight. Now this might not be a true SAS procedural assistance but wanted some advice before i could start building the analysis.   While all these dep var are significant with the predictor variables hence does building a linear regression model require that some of the predictor variables have to be insignificant else if all are significant we can do a correlation analysis and see how the variables are related rather than following the entire process of regression.   Kindly advice as this is what i got to know from one of the analytics practice lead. ... View more

Dear All, i am on one of the courses offered from the SAS institute for learning & taking some clues which i will further add to one of my projects. this should be an easy fix i am guessing.   KIndly see the code that i have built: proc reg data = statdata.bodyfat2; model PctBodyFat2= age weight height neck chest abdomen hip thigh knee ankle biceps forearm wrist /selection=backward; id weight; run;   As we all know the the elimination method will throw insignificant var one by one. My question here is that along with the elimination method i need to add "p" that calculates predicted values for a given value of x. Hence the code should look like   proc reg data = statdata.bodyfat2; model PctBodyFat2= age weight height neck chest abdomen hip thigh knee ankle biceps forearm wrist/p /selection=backward; id weight; run; However this throws an error. Kindly let me know if this is doable.   Regards, Shivi ... View more

Dear Team, I am working on a collections assignment for one of my clientele.   The requirement is that they need to analyze how's the pay pattern of customers and who are a pain area.   For this i have started with creating day level drill down of customers based on payment days. so customers make payment from a period of 10 days to over 1000 days. so i used a case statement and created various segments with respective population.   The challenge i have now is that since this data is for past 1 year hence there are instances where a customer (SFX code) might have made a payment in 10 days whereas the same customer would have made the payment in 50 or 100 or even more days. Hence i need to know % payments made within x number of days.   I could have created a new var as total where total = category + category 2 (first 2 lowest categories)/ total = x% and then i could have filtered however as these categories are calculated columns hence i cannot use this as well. Request you to please suggest an alternate.   Attached some data for examination.   Regards, Shivi ... View more

Dear Team,   I have working on a data which has 1 million observations. This data contains the phone numbers of our customers. During the booking process the resources enter the phone numbers of our clients however there are many instances where an incorrect phone number has been entered lets says "9999999999". <this is an india format with 10 digits and no country code>.   I have run proc freq on this data and can see there is approx 19.5% of the data which is incorrect i.e. in the format like "9999999999", "1111111111" etc which are written in varuous ways. I need to delete this data and only keep the valid phone numbers.   running if delete statement would have done the trick however as i mentioned the ph number is written in various ways (all numeric).   Kindly suggest an easy way if possible. I am working on SAS developer.   Regards, Shivi ... View more