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MATH38172 Generalised Linear Models
创建日期：2024-05-25 16:41:07
所属分类：数学mathematics
标签： MATH38172
Generalised Linear Models

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MATH38172 Generalised Linear Models

Coursework 2023
Instructions. Attempt the questions below and submit your work online via Blackboard by the deadline of
3pm on Friday 28th April 2023. Your submission must be a single file. It may contain any sensible mix of
word-processed and (scanned) handwritten parts, for example using LaTeX, RMarkdown or Microsoft Word.
You should include any R code used. A complete solution is possible in 5 pages of type 10 font; please limit
your response to 10 pages at most. The coursework may take up to 10 hours to complete. The submitted work
MUST be your own. Plagiarism will not be tolerated and will result in serious consequences if discovered.
Background. The file smokingdata.csv on Blackboard contains data on the relationship between smoking
and health for 1314 women in Northern England. The women are grouped according to the combination of
levels of two variables:
• Age: the women’s age in the initial survey in the 1970s (categories: 18-25, 25-34, 35-44, 45-54, 55-64,
65-74, 75+);
• Smoking: the women’s smoking status in the original survey (categories: NonSmoker, Smoker).
For example, one group is the set of women who were non-smokers aged 25-34. For each group, the following
two variables have been collected:
• Alive: the number of women in the group that were still alive 20 years after the original survey;
• Dead: the number of women in the group that were dead 20 years after the original survey.
Questions
1. Read the dataset into R. (1 mark)
2. (a) Fit a logistic regression model to explain the probability of death within 20 years, using smoking
status as the ONLY explanatory variable, and present the summary for the fitted model. (1 mark)
(b) Write down the fitted model in equation form and interpret its parameters, including the parameter
values. Do you notice anything unusual about the parameter estimates? (3 marks)
3. (a) Fit a logistic regression model to explain the probability of death within 20 years, using BOTH
age and smoking status as explanatory variables, and present the summary for the fitted model.
(1 mark)
(b) Write down the fitted model in equation form and interpret its parameters, including the parameter
values. (3 marks)
(c) Compare your answers in 2(b) and 3(b). What do you notice? What is the reason for any
dierences? (3 marks)
(d) Assess whether there is significant evidence that the probability of death depends on (i) smoking
status, or (ii) age. Give details of which tests are used, equations for the test statistic, critical
value, etc. (4 marks)
4. (a) Using the model you fitted in Question 3, estimate the probability of death within 20 years for a
woman aged 55-64 who does not smoke. (1 mark)
(b) Find a 95% confidence interval for the probability in 4(a). Explain your working. (3 marks)
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关键词一 关键词二 关键词三 关键词四 关键词五 和法规和的发更好的风格和 ECON 615 FINC 612 CSC148 COMP 639 ACCT 203 ACCT 211 PSYC 101 MTH2009 COMP52315 PSYCO 432 statistics MATH4063 11 xxx 1 MA1MSP MAST30028 MATH3888 CS341 EEE30002 ES2F5 MCD4160 CC0933 ECON 1101 MCHM3001 CHEM3118 COMMGMT 2511 COMP41280 STAT 631 24T1 IRE379 SENG365 ECON433 FIT3139 MATH4602 LING5621M FINS5516 ECON3208 MN2177 L2 SM EEET1415 Finance DS4023 COMP3004 7CCSMRTS K1S5B6 Stat230 CSCI4211 CSI2132 ECON30130 MAS6100 ENVS222 COM2107 INFO1112 STAT 4004 FIT2100 comp2022 COMP4691 Physics 307 Econ 659 probability CSCI316 fir29 CSCI203 COMP3160 COMP6714 INFO1113 Physics 7B Physics Photonics S203031 STAT2005 COMP90015 CSCI 2110 CSCC46 Information CSC477 COMP4650 Statistical COMP 346 COMP1017 ELEC340 MATH1007 Programming function STAT 244 CS 134 Java cse13s Math 108A FW20 ECON3389 CSE 130 Science 331 COMP9020 engineering COSC 445 CSE 5523 GAME2012 visualization MATH 235 Math 370 CSC343 COGS 108 EE524 COMP10200 STAT 416 3FK4 MSCI 311 ECON6113 ACC40700 EMESTER1 MAS8383 ECO 512 STAT 8310 CMN3102 MA577 CMPT 225 COMP0045 Methods Equations MATH 113 Math 3283W ICS-33 EN4302/ENT603 BIA B350F MA318 MTHM506 MECH 5315M ECONOMICS MAS8382 COM 2004 PX3142 XJEL 3662 STAT 231 MGT B399F PX4131 COM2108 30AM MSCI521 ECONM1015 ACFI304 GR5241 MATH10101 ECON 2070 COMS31900 EFIM20011 CSE 250B ACSE-5 STAT4207 SOFT2412 ELEC 331 AY2020 MSIN0209 FIT2094 CS 241L ST404 CS 411 3D CA3 INF4002 COMP3506 SIT718 CS 188 CS 170 MATH 138 CSE 251A CMT118 DATA5207 CMPT307 CMPT459 T1 PGEE11108 COSC 3P32 ME 163 MATH96007 7QQMM203 EE6227 BA 574 STA 4234 ECO206Y1Y ECO2008 MT2300 MATH 11158 CS 527 MACM 316 CSE474 2DI70 ISE 525 COMP3411 EMAT30007 7CCSMBDT MFIN704 MFIN704W21 MfIB ECE 438 CS 436 F36 CS5344 FE 621A FE621 TBA 612 ECM3151 ECMM422 MF1 MSIN0107 ESSMENT CS 5854 MFIT 5008 MIPS R4000 ENG5274 BU52018 ENG2079 BIOA02 STA2570 F0 INF553 STAT 440 STAT3008 COMP9417 COMP6451 6COM1042 BU52006 ST303 HW-1 CISC-235 CS 510 MATH3161 ECN 140 ECE391 Comp 3613 CVEN 9625 PRG455 UESTION 1 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