++++++ Ask your QM3 question here and a Success Formula tutor will answer it as soon as possible ++++++ Any problems or questions while studying/preparing for QM3? Don't worry, we got you covered! Just post any of your questions in the QM3 course on StudyDrive and our tutors will help you! We are also offering a 3h Crash Course for this course in which we will go through all the cases and exam-like questions! We will be checking in daily as of Monday, 20.01. :) PLEASE ask your questions as a SEPARATE POST and NOT as a COMMENT here! We wish you lots of success! Your Success Formula Team
When is this crash course?
We offer them every days actually. You can see all the spots left on our website. We are actually getting more bookings than we expected based on the last days so we are trying to also open more classes.
This might be a potential bonus point for QMIII, so it might be usefull to start complain about this one ;)
Q4 and Q7 are neg. cor. too, or?
Yes :) bc of the minus sign
Thanks 🙏
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Get that iPhone girl!! ;)
ahah I hope I will ;) txs
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Where did you get the values for g-i from?
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No the text says that each different colour requires an additional 0.6 minute setup. Since we know that 1.2 minutes = 0.020 hours we can just divide this number in half to get the 0.01 :)
🤦🏽‍♀️ omg thank you 🙏
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Carlo Steinbach lädt was bei Studydrive hoch... Jetzt hab ich wirklich alles gesehen :D
Und was für eins!
where does the 0.844 come from?
influence of tangible on satisfaction (from another test)
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Great summary! That iPhone is mine though...
Thanks! Good luck to both of us ;)
For Spearman’s rank correlation does it have to be two ordinal variables or is one enough?
No they both have to be at least ordinal. Interval and Ratio is also okay but then you would lose information because of "downgrading"
Where did you get this number? I can't find it any where
my mistake, it should be 0.076 (Se of tangibles)
more precise frequencies are used for qualitative variables (nominal and ordinal), whike descriptives are used for all quantitative variables (interval and ratio); and for likert scales you can also apply descriptives as well since it can be regraded as pseudo interval
why is 23 B? (17-18 first)
b) because B is right due to the definition you can see above (if you recall from the case it was just that every colour ads an additional amount of PU but in the end its the same for all colours --> same coefficient but the more colours you add the higher your result is) and B is just a special case of D where y1 would be 0.
So do you apply frequencies on a variable that is measured with a likert scale? Because strictly seen it is ordinal so you would do that, but if you would see it as pseudo interval you could also use descriptives...?
I have been struggling with Case 6 a bit, does anybody have a complete solution ?
Lou uploaded one :)
example: - relation between the size of firms (as measured by Q21), and their technology level (as measured by Q22).
another example: whether, on average, firms are more interested in technical assistance (as measured by Q4), or in assembly assistance (as measured by Q7).
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why u not verder dan m
mistake from my computer. it was erase for no reason
i) i: where do you get those values from?
you have to look at the H2 and for instance: for the start: a dummy which starts from zero, becomes one in the year in which an ERP implementation is started, and remains one
Thank you 🙏
I don't understand how you can have more adopters than firms? Should we also divide the adopters by 13?
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You‘re welcome :)
1849 distinct firms in the dataset (24,037/13) 313 of those firms are adopters (4069/13) correct that way! thanks :)
But only for the Levene´s test. but nevertheless thank you for the summary!!
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Katzengott - Carlo
where is that from?
I got 0.025 (pretty sure its just a rounding difference) and it is from the regression output of MACH against MACHSchenkel under "Coefficients".
By saying log(pretaxincome)=adpoter*.133+log(asset), do they mean ln(pretaxincome)=adpoter*.133+ln(asset)? Thanx
yes, exactly. In this case log is the natural logarithm.
Where did you get -0.029 from?
ln(0.971)= -0.029428
you do it to get rid of -0.029*log (on the left side). I hope it helps :)
Hahahahahaha
Question for succes formula: why 13c 14D? (exam 13-14 1) (v:CP)?
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thanks!
same exam, why Q25 is D?
Could somebody could please quickly ecplain me how to set up the confidence interval here?
Where does this value come from?
The number comes from b) III but there happened a small error by denoting the number. It should be 18,385.0008. The result should be correct, tho.
Thank you :)
If you have any questions, please feel free to post them now! I am online for the next hour :D
How do you draw the sketch? :)
Hi! What I did to create the 'two periods', is to first delete the observations 106-192, then run the regression which will give you the result for 'period 1', and then I did the opposite, so delete the first 105 observations and run a regression to get the results for 'period 2'. Hope this helps
Where do you have to go in SPSS to split the file into the two different sets of periods? Thanks
You have to cut period one ( save it). Work with P2 and then go back to P1
How do you define this Variable? I understand how to get the Break_Dummy variable but am absolutely clueless what else i should do
The Break interaction variable is breakdummy*market Return
I got 9919.069 for SSEr... did I do something wrong or?
Not sure. I might have fucked up as well. It's very close to what I got though so your f should be around 0.1 as well, You'll fail to reject by a huge margin and the outcome is the same.
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You're an angel!
Hey guys, I will be coming online tonight between 6:30PM and 7:30PM to answer questions. Feel free to stack up some questions until then and mention me into them so it is easier for me to see :)
I answered all the old exam questions I could see. I am off for today. Daniel is going to come on tomorrow from 17:00 to 18:00. Feel free to send questions until then :)
Could anybody explain me why it´s B? I understand why claim 2 is correct but not why 1 is incorrect? Also the answer in the answer key does not really make sense to me, so help would be really much appreciated! Thanks
You will have missing data in Assur5 vs 6. Assur5 can only be answered by people that actually made a telephone contact while assur6 can be answered by everybody. This info is also in the text of q9.
Are you sure it is the right answer?? Because my answer is around 3.1695 which means that the Ho can be rejected at 10% (2.33)
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True! thanks for telling me :)
the problem is that you should substract (0.366-0.354) and not devide it as you did :)
Hello, I need your help smart students, i have to do the course assignment for qm3, and i m struggling (just a bit). Maybe someone can do it for me and I´ll pay... of course. Thanks
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Nice work!
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Thank you and are you gonna upload the sixth case too?
Right now I’m rather working on past exams but as soon as I finish case 6 and feel confident that it’s about right I’ll post it
AHAHAHAHAHAH
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You saved me, thx Leo. Hope you get that iPhone :p
So when the means are NOT the same (H0 can be rejected), this would mean that there IS a relationship between them?
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How did you define MACHall at F?
It’s just like in the H0 clr1 + 2*clr2 + 3*clr3 etc (if I’m not wrong because I don’t have it in front of me right now)
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hey thank you! at k) how do you compute the dummy variable, once you're in the recode to different variable tab, what do you do? Thankssss :)
Just put 1 for the value that you make the dummy for and for all else 0
How do you calculate the SSEr? Because I get that you take the SSEc out of the info?
why is the answer B? Anyone know :)?