İptal Edildi

Mixed Between-Within ANOVA analysis

Two experiments have been carried out.

The first experiment consisted of 23 drivers doing "Task A" for 18 trials. Two performance measures were recorded during each trial (Speed and Error)and recorded in two tables. Therefore, each subject has 18 records in speeds and 18 records in Error table (repeated measures). Two more attribute also added to each row (subject) at the end of this task ("TS" and "AS" to Speed table ; "TE" and "AE" to Error table). These are already calculated based on driver's performance and available. As a result in total there are 20 numbers associated with each subject, however the last two columns are not part of our repeated measure and should be considered as separate values, we just put it in that table to wrap all the information up.

(PLEASE REFER TO PICTURES ATTACHED FOR TABLE FORMATS).

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The second experiment consisted of 27 totally different drivers. They first practiced on a different "Task B" and based on the result of this test, each driver was assigned to one of the three following groups: "A, L, NA" . Maximum Speed (MS) and an ALPHA value was also assigned to each driver based on their performance. Therefore, each subject has three attributes : {A or L or NA}, ALPHA and MS.

Then these subjects are asked to do "Task A" for 18 trials. Again Speed and Error was recorded for each trial for all drivers and the same tables were created as before.

Analysis required

A within-between ANOVA analysis (or anything better if you can convince us) is needed based on the tables mentioned above. It is to analyze the impact of "Task B" on "Task A". For example: those who were categorized "L" in "Task B" were X% more likely to have less TS and AS on Task "A" in compare to those who had not driven "Task B".

It is simply to evaluate how practicing a "Task B" can improve/change the performance measures of "Task A".

It needs to be comprehensive and should include a few paragraphs in plain language explaining the impacts. All the details of the measure names, etc will be given for the purpose of write up.

All mentioned tables are ready in Excel format.

If you are an experienced statistician, we expect it takes you 1 hour to understand the experiment method and how it was done and 1-2 hours to do the math and ~1 hour to do the writeup.

Thanks for looking and let us know if you need further clarification.

NOTE: "Task A" is comprised of two sub-tasks each repeated 18 times. Therefore, there will be two tables for "Task A" which have the same characteristic as mentioned above. We just did not want to make the description complicated. In a sense there will be two tables for "Task A1" and two tables for "Task A2". No correlation analysis required between these two, we only want to know the impact of "Task B" on "Task A1" and "Task A2" separately. Methodology will stay the same, only repeated for two sets of tables.

Beceriler: Veri İşleme, Pazar Araştırması, Matematik, Matlab ve Mathematica , İstatistik

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İşveren Hakkında:
( 7 değerlendirme ) Toronto, Canada

Proje NO: #687595

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PerfectSquare

Please see the PM

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SquareRoot

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jackie235

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dineshjohnson

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proffsg

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pabna

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maraovidiu

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researchwhiz60

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hmanhertz

I have conducted many analysis like this in projects for companies lookig to understant differences in market initiatives. I would be happy to discuss further this project wit you..

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