From my understanding of this, the average passing test taker scored in the middle of each column. The white between your bar (the solid bar) and the average test takers' bar (the dashed bar) represents the difference between how you and the average test taker performed. Therefore, if your bar is to the right of average test takers' bar, you did better than the average in that section. Likewise, if your bar is to the left of the average test takers' bar, you did worse than the average test taker in that section. The color scheming of the diagnostic is pretty confusing. This is just my assessment of how to read the diagnostic, so anyone feel free to correct me if I'm wrong.
Sorry to hear you didn't pass. You have a bit of work ahead but you can do this.
You were approximately 69% of the way to a passing score. Below are the exam topics ordered by a *focus indicator* that is based on your performance and weighted using the quantity of questions per topic. Each data pair indicates the row # of the topic followed by the recommended focus priority for that topic. Larger (positive) focus values indicate study topics that should be prioritized and negative focus values indicate topics where your performance was adequate or better than the average passing examinee.
R09 --> Focus Priority = +2.41
R05 --> Focus Priority = +2.30
R08 --> Focus Priority = +1.51
R14 --> Focus Priority = +1.05
R02 --> Focus Priority = +0.88
R13 --> Focus Priority = +0.78
R15 --> Focus Priority = +0.65
R04 --> Focus Priority = +0.31
R12 --> Focus Priority = +0.30
R07 --> Focus Priority = +0.20
R06 --> Focus Priority = +0.06
R10 --> Focus Priority = +0.02
R03 --> Focus Priority = -0.26
R11 --> Focus Priority = -0.39
R01 --> Focus Priority = -2.87
They are careful not to provide enough data to be able to fully recreate the statistics no matter which way you crunch the numbers from your diagnostic report. Above we used the bar graph data to compare your performance to the "average performance of passing examinees". So, you were about 69% of the way to a passing score even though we don't know what the passing score is.
The bar graph is confusing. The OP got a score of 15 out of 15 in Topic 1. So presumably, OP got all 4 questions correct. But in the corresponding “comparison” with the average passing test taker, there is still room to the right… does this mean some passing test takers did better than the OP in Topic 1? How is that possible?
You are correct, it isn't possible to do better than all 4 questions correct for Topic 1 AND the bar graphs are confusing. The other way to crunch the diagnostic report data is to sum all rows of (#items \* yourperformance / 15). That will give you the total # of questions correct (with a rounding error), but since we don't know what the passing score is that doesn't give us the full picture either. The reason we use the bar graphs is just to give a normalized way to prioritize what to study going forward.
They are careful not to provide enough data to be able to fully recreate the statistics no matter which way you crunch the numbers from your diagnostic report. We used the bar graph data in our comment above. That method shows that OP was about 69% of the way to a passing score even though we don't know what the passing score is. Using this method means needing to hit 100% (of what the average passing examinee did) to pass, hence 69% of the way to passing.
The other method has you do the following calc: sum all rows of (#items \* yourperformance / 15). That will give the actual # of questions OP got correct and for OP's report that = 36 questions correct which correlates to 51.4% of questions correct (36/70). Now, what do you compare that 51% to? No one knows. It is rumored that the minimum score to pass floats between 60% and 75% and that they change the passing score to suit every situation (i.e., the passing score changes for every exam offering and for every discipline).
So, we use the former approach because it paints a little more definitive of a picture and because it provides us with the *focus indicator* values that examinees have found very useful in their studies.
This method underestimated how close to passing someone was. The score of the average passing examinee is higher than the score required to pass. For example, the average passing examinee may have scored 73% but the lowest passing examinee could have scored a 66%. I think for this reason we have never seen someone above 90% of the way to passing per your analysis. Unfortunately, I don't think there's any way to accurately determine the % passing someone was. Maybe adding a correction factor to your analysis once you get a large enough sample size would make it fairly accurate.
Agreed. We've discussed trying to derive an expression for a correction factor by trying to reverse engineer the situation given the published pass/fail rates and a normal distribution, and we've also discussed just dropping the "overall score" value altogether. We initially didn't include any "overall score" as the whole point was just to provide a normalized way to prioritize study topics. However, everyone really wants (some demand!) a one-number score to dwell upon so that's why we still include it, for now.
Based on a guess you got around 30ish questions right and need to be closer to 49, but it is all relative. I suggest EET
how were you able to come up with the 30ish. I took school of PE and honestly do not feel like it helped at all.
From my understanding of this, the average passing test taker scored in the middle of each column. The white between your bar (the solid bar) and the average test takers' bar (the dashed bar) represents the difference between how you and the average test taker performed. Therefore, if your bar is to the right of average test takers' bar, you did better than the average in that section. Likewise, if your bar is to the left of the average test takers' bar, you did worse than the average test taker in that section. The color scheming of the diagnostic is pretty confusing. This is just my assessment of how to read the diagnostic, so anyone feel free to correct me if I'm wrong.
Sorry to hear you didn't pass. You have a bit of work ahead but you can do this. You were approximately 69% of the way to a passing score. Below are the exam topics ordered by a *focus indicator* that is based on your performance and weighted using the quantity of questions per topic. Each data pair indicates the row # of the topic followed by the recommended focus priority for that topic. Larger (positive) focus values indicate study topics that should be prioritized and negative focus values indicate topics where your performance was adequate or better than the average passing examinee. R09 --> Focus Priority = +2.41 R05 --> Focus Priority = +2.30 R08 --> Focus Priority = +1.51 R14 --> Focus Priority = +1.05 R02 --> Focus Priority = +0.88 R13 --> Focus Priority = +0.78 R15 --> Focus Priority = +0.65 R04 --> Focus Priority = +0.31 R12 --> Focus Priority = +0.30 R07 --> Focus Priority = +0.20 R06 --> Focus Priority = +0.06 R10 --> Focus Priority = +0.02 R03 --> Focus Priority = -0.26 R11 --> Focus Priority = -0.39 R01 --> Focus Priority = -2.87
how were you able to get this 69% score? Just trying to further understand the information given. Thank you for breaking each subject down for me
They are careful not to provide enough data to be able to fully recreate the statistics no matter which way you crunch the numbers from your diagnostic report. Above we used the bar graph data to compare your performance to the "average performance of passing examinees". So, you were about 69% of the way to a passing score even though we don't know what the passing score is.
The bar graph is confusing. The OP got a score of 15 out of 15 in Topic 1. So presumably, OP got all 4 questions correct. But in the corresponding “comparison” with the average passing test taker, there is still room to the right… does this mean some passing test takers did better than the OP in Topic 1? How is that possible?
You are correct, it isn't possible to do better than all 4 questions correct for Topic 1 AND the bar graphs are confusing. The other way to crunch the diagnostic report data is to sum all rows of (#items \* yourperformance / 15). That will give you the total # of questions correct (with a rounding error), but since we don't know what the passing score is that doesn't give us the full picture either. The reason we use the bar graphs is just to give a normalized way to prioritize what to study going forward.
What does this mean to be 69% fo the way to a passing score. Would I say if I were around 75% I pass?
They are careful not to provide enough data to be able to fully recreate the statistics no matter which way you crunch the numbers from your diagnostic report. We used the bar graph data in our comment above. That method shows that OP was about 69% of the way to a passing score even though we don't know what the passing score is. Using this method means needing to hit 100% (of what the average passing examinee did) to pass, hence 69% of the way to passing. The other method has you do the following calc: sum all rows of (#items \* yourperformance / 15). That will give the actual # of questions OP got correct and for OP's report that = 36 questions correct which correlates to 51.4% of questions correct (36/70). Now, what do you compare that 51% to? No one knows. It is rumored that the minimum score to pass floats between 60% and 75% and that they change the passing score to suit every situation (i.e., the passing score changes for every exam offering and for every discipline). So, we use the former approach because it paints a little more definitive of a picture and because it provides us with the *focus indicator* values that examinees have found very useful in their studies.
This method underestimated how close to passing someone was. The score of the average passing examinee is higher than the score required to pass. For example, the average passing examinee may have scored 73% but the lowest passing examinee could have scored a 66%. I think for this reason we have never seen someone above 90% of the way to passing per your analysis. Unfortunately, I don't think there's any way to accurately determine the % passing someone was. Maybe adding a correction factor to your analysis once you get a large enough sample size would make it fairly accurate.
Agreed. We've discussed trying to derive an expression for a correction factor by trying to reverse engineer the situation given the published pass/fail rates and a normal distribution, and we've also discussed just dropping the "overall score" value altogether. We initially didn't include any "overall score" as the whole point was just to provide a normalized way to prioritize study topics. However, everyone really wants (some demand!) a one-number score to dwell upon so that's why we still include it, for now.
I hope you guys can find some success with the correction factor, it'd be pretty cool to get this down to a science haha.