This week, we kept the DI homework lean, and focused exclusively on Data Sufficiency, with an emphasis on DS questions that align with certain quant topics.
So for now, all of this will sound a bit like the guidance we offered for the quant section. Don’t worry: all of this will evolve once we get to the other four DI question types (GI, TPA, TA, MSR, LSD, FBI, EIEIO, etc.).
Benchmarks for Your Week 2 Data Insights Results
Before you do anything else:
- Count the errors that make you go "whoa, how the 🤬 did I miss THAT one?!?" No really: count them, for EVERY Data Sufficiency set you completed. Then divide that by the total number of questions to get your careless error rate.
If your long-term goal is to score in the 80s, here are the metrics I’d like you to hit in Week 2:
- Careless error rate: < 5%. If you make careless errors on 5% of questions now, you’ll make far more under the pressure of the actual exam – maybe three times as many. And that will destroy your score. So please get this careless error rate down to 1-2% at most.
- OG & Data Insights Guide sets (#2 on the list): 85-90% correct is excellent, 80% is probably good. Just remember that WHAT you miss is more important on the GMAT than how many you missed: careless errors are apocalyptic. If you missed OG questions on topics that you haven't studied, that's totally cool -- you'll have time to learn those things.
- Randomized batches of forum questions (#3-4 on the list): 85-90% correct is good on the sub-555 questions, but if you did mixed difficulty sets, you’ll have to take the results with a grain of salt. If you happened to see nasty, strange questions, 50-60% might be pretty good. Don’t overreact if the percentage wasn’t great, though.
- Speed: On the OG and topic-based sets, you're in good shape if you’re reasonably close to 2 minutes per question. If you're slower than, say, 2:30 per question on average, it might be a sign that your basic skills are rusty, or that you're not choosing efficient paths forward -- and you'll be able to improve those things over time.
What Should You Do About Your Data Insights Weaknesses in Week 2?
Our usual reminder: you can miss plenty of hard DS questions, and get an excellent score, but if you make careless mistakes on easier questions, the GMAT will eat you for breakfast.
So when you study, please pick your battles wisely. If you’re painstakingly reviewing every single question you missed, you’re probably missing the point.
Yes, you’ll want to look for signs that your overall approach to DS questions is shaky, or that your quant foundations need strengthening. But if you’re getting abused by hard or obscure questions? That’s cool. Don’t waste too much of your precious study time on that stuff.
Here’s some guidance on what to do once you’ve analyzed your results:
- If your careless error rate is too high: address this problem ASAP. Nothing else matters on quant until you do. Check out the resource lists in the study plan for help.
- If you struggled with the overall process for answering a Data Sufficiency question: check out this LIVE video on the DS process or this (not-so-live) DS video.
- If you struggled on specific topics: (algebra, arithmetic, etc.), don’t panic. It’s far too easy to overreact to a few errors, and study these problems until your corneas crack. Instead, try to put your struggles in context: did you miss particularly hard or strange versions of these questions? Were your errors careless? If so, you probably don’t need to do much studying, exactly. But if you missed basic questions because your foundations are shaky, then you might need to do some remedial studying, and it might even make sense to “pause” the study plan to do so – but don’t assume that you need to do this unless the data is very, very clear about your weaknesses.
- If you struggled on the OG or Data Insights Guide sets: don’t panic. Again: ask yourself WHY you struggled. If you’re at, say, 70-80% accuracy, that’s not ideal right now. But context matters: if most of those errors are on topics you’ve never really studied, you’re in great shape, since you have plenty of time to learn those in the next 11 weeks.
- If you got CRUSHED by ALL of the homework: if you’re nowhere close to the benchmarks on Data Sufficiency – and if your long-term goal is a DI score in the 80s – then maybe you need to back away from the study plan, and invest some time in rebuilding your basic quant skills. If that’s the case for you, tag us in the thread, give us as much detail as you can about your situation, and we’ll try to help.
- How much time should you spend reviewing individual Data Sufficiency questions? Not much, please! Because it can take SOOOOOOO much time to review a question, it should be your absolute last resort. That’s why we want you to redo questions first – sometimes, you’ll see your mistake right away, and that’s the best way to learn. If you miss a question a second time, then maybe it’s a sign of an underlying issue.
- No, really: resist the temptation to obsess over individual questions. Instead, look for patterns in your errors – an error on one question might be a fluke (or a weird, hard, or badly written question), but if you miss several related questions, you have an opportunity to get a good ROI on your study time by addressing a general weakness via a video or articles or books.
Hey, I warned you this would be very similar to the quant section. It will all look different once we start working on the other DI question types in the coming weeks. Enjoy the calm before the DI mayhem really begins!