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Statistics 140SL Task 3 January 21, 2014 Introduction This task is due 1/27/2014 (Monday) via upload as an R script to CCLE in Week 3 before 11:...

i need help with this assignment , it's to write a Rscript to build two model based on the data given and give discussion and explanation
Statistics 140SL Task 3 January 21, 2014 Introduction This task is due 1/27/2014 (Monday) via upload as an R script to CCLE in Week 3 before 11:55pm. Please make sure it compiles correctly from any computer with R on it and not just your own personal one. Data and Question The data for this assignment can be found at http://www.stat.ucla.edu/ ~ vlew/datasets/stat140sl/ task3data.csv . There are 12 variables in the data set: 1. V1 pregnancy weeks at interview ( less than 17) 2. V2 1 if fetal death, 0 if not 3. V3 mother’s age at conception 4. V4 number of previous spontaneous abortions (0,1,2,3+) 5. V5 0 if no previous children, 1 if 1+ 6. V6 gestational weeks at end of pregnancy (less than or equal to 17) 7. V7 smoking 1:0, 2: between 0 and 10 cigs/day, 3: 11+) 8. V8 number of weekly drinks during pregnancy 9. V9 coffee consumption during pregnancy (0:0, 2: 1-7 cups/day, 3: 8+) 10. V10 childs length in cm 11. V11 birth weight in gram 12. V12 number of fever incidences before interview Please answer the following question using the lm() function in R. Submit your R code as your answer and please use comments at the end of your R code to interpret your results: If the fetus small for its age (in weeks) what variables are related to size? To do this you should use a combination of V10 and V11 to define small (you will define small, not I) and then decide what variables are related to being small. 1
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Assignment I do not expect you have a perfect or complete answer for this problem and I do not expect you to fully solve the possible problems that may arise. This question is rather open ended to help me determine things about your ability (or lack of ability) to solve a problem. You may seek help from others and you may work with classmates, however, your submission must be unique (otherwise, you’ll invoke the academic dishonesty penalty). If you are unable to do this assignment, no problem, you’ll just get an additional Task 3 next week. What you are required to do is: 1. Submit two different models and write down why you choose to do the things that you did (e.g., why did you include or exclude certain variables). The models do not need to be completely different, but I am asking for two because you might be uncertain as to which one you like better. 2. Discuss assumptions on which the analysis is based and justify your assumptions. For example, if you decide to transform a variable, you should be able to explain why you did such a thing. 3. If (and only if) problems arise, identify them and potential solutions. 2
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