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MATU9D2: Practical Statistics
创建日期：2024-09-14 17:58:04
所属分类：统计学statistics
标签： MATU9D2
Practical Statistics
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MATU9D2: Practical Statistics
PROJECT 2
Report
• Write a report to include answers to both questions. Your report needs to be typed using a text editor
(such as Word) with the relevant Minitab output and plots copied and pasted into the document.
• The report should be no more than 20 pages long.
• Marking of the project is performed anonymously. Do not include your name either within the report
or in the filename of the report. To identify your submission, include your student number at the
start of your report, and in the filename of your report.
• Convert the document into a pdf file prior to submission.
• The grade for this project counts towards 20% of the final grade for the module.
Each answer should include:
1.
Description of the sample data including the study variables, design and study units.
2.
Details of the research question.
3.
The choice of the hypothesis test with justification.
4.
Exploratory data analysis including:
- appropriate summary statistics from Minitab.
- appropriate plots from Minitab with interpretation.
- any comments regarding trends in the data to support the research question.
4.
The null and alternative hypotheses of the hypothesis test.
5.
Details of the formal statistical analysis including:
- information on the test statistic and the underlying distribution.
- relevant Minitab output for the test.
- the test statistics, p-value and/or confidence intervals with appropriate
interpretation.
6.
Test decision and conclusion.
7.
Assumptions of the hypothesis test including:
- details of the assumptions.
- relevant Minitab outputs with interpretation.
- conclusion.
8.
Summary of results and further comments if any.
Statistical analysis
All statistical analysis must be conducted in Minitab.
Submission
1. Late Submission Regulation 6.2.8.2: At undergraduate level, coursework will be accepted up to seven
calendar days after the submission date (or expiry of any agreed extension) but the mark will be
lowered by three marks per day. After seven calendar days, the piece of work will be deemed a non
submission and will be given 0 (Saturday and Sunday count as two calendar days)
Work which is submitted for assessment must be a student’s own work. All students should note that
the University has a formal policy on plagiarism which can be found by following this link.Q1 (25 marks)
Oxygen consumption rates of two species of limpets, Acmaea scabra and Acmaea digitalis, at 3
concentrations of seawater was measured (μlO2/mg dry body weight/min at 22ºC). 8 replicates per
combination of species and seawater concentrations were considered and the results were as
follows:
At 5% level of significance, test for interaction and main effects of species and seawater
concentrations on oxygen consumption rates. Conduct the appropriate test and report all the
relevant analysis to investigate the research question.
[Question 2 overleaf…]Q2 (25 marks)
The following data were collected during a study involving patients with cystic fibrosis. The
variable of interest is PEmax (maximum expiratory pressure) which is a good measure of
malnutrition. The explanatory variables measured are age, gender, height, weight, BMP, FEV1, FRC,
RV and TLC. Several of these variables relate to lung function or body size.
The aim of the study is to identify from the possible explanatory variables a model which
predicts PEmax well and also to assess how well the 'best model' predicts PEmax.
The dataset is saved in the file PEmax.csv and can be downloaded from VLE. The dataset contains
11 columns (including subject number which should not be used in analysis) and 52 rows. You will
need to download the data file from VLE save it onto your drive and then open/copy the data in
Minitab.
Fit a multiple regression model to the whole data to identify the explanatory variables that are
associated with PEmax, investigate the potential issues of the full regression model then perform a
model selection to identify the best model and report the results.
案例分类
标签云
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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