Mathematics Test Tips

Making Mathematics Easy



FOR PAPER & PENCIL TESTS

There is usually a Percentage of incorrect answers that are deducted from you total score, so you must be very wise in guessing. Your strategy is to maximize your score in the time permitted, without incurring penalties.

As you go through the problems:

 Work in the test book. Use any available blank space for figuring, as needed. Circle your answer choice
 Also write the letter of the answer choice next to the problem number.

On each section, you will be told how many minutes you have for that section.

Note what time you start, and figure the time at which you have to complete that section. For example, if you start a section at 8:37 and you have 25 minutes, time will be called at 9:02. Now subtract 3 minutes from that time. Write that time down so you will know when you need to stop working problems and start filling in the answer sheet or grid. In our example, that would be 8:59.

You will be filling in the answers on the blanks or grid during the last three minutes, so do not put anything on the answer sheet as you are working problems.

Do the problems in three waves:


1. First wave:

 

  • Do the ones you know how to do and can do quickly.
  • Star any problems that you think you know how to do, but will take more time.
  • Circle any problems that you don’t know how to do. If it is not a multiple-choice problem, guess.
  • There is no penalty for guessing on these short answer types.


2. Second wave:


 Return to the problems that you starred. These are the ones that you’re fairly sure you can figure out, but that need more time. Typical of this level of problem would be the ones in which you must try all possible answers to eliminate the incorrect ones.

3. Third wave:

Spend what time you have remaining (not including your last three minutes) working on the problems. Up to now, you have maximized your points given the time constraint. On multiple-choice problems, if you can eliminate at least one answer as incorrect, guess. If you cannot eliminate at least one of the choices, it will be better not to guess. If there is no penalty for incorrect responses, then guess freely.

When you have used up all your time but the last three minutes, stop working. Use the last three minutes to fill in your answer sheet, and check it at least once to be sure you have marked the correct response for each problem. You may be able to check them all twice.

The PSAT and SAT usually have the questions roughly in order of difficulty. If you have 30 questions, you can be pretty sure that by number 18 or so, you will not find but a few problems that you can do very quickly and easily. Keep this in mind as you progress through the problems. If there are 30 questions and you find that number 27 is a "snap," you may be jumping to conclusions and/or not really understanding what the problem is asking. Be very wary of "obvious" answers more than half way through the section. It would be better to mark it with a star and come back to it.

Put down your pencil and relax until the next section. You have done your best.

Try these techniques on the following group of problems.

1. FOR COMPUTER-BASED TESTS

For tests taken on a computer, you need to find out if you will be able to skip problems and then go back to them.

If you cannot go back after skipping problems, there usually is no penalty for guessing. (Ask about penalties for incorrect responses.)Just work each problem as quickly as you can, being careful to not spend more than 3 minutes on any single problem. Rather than use a lot of time on one problem, it will be better to guess and go on, so that you can at least try all the problems.

If you can skip and go back, ask about penalties for incorrect responses. Then number a sheet of paper 1, 2, 3,…., 25, or however many problems are in this section. This will be how you record the ones you need to go back to. You will be entering your answer choices on the problems as you go, so there is no need to save time at the end for recording answers.

On each section, you will be told how many minutes you have for that section. Note what time you start, and figure the time at which you have to complete that section. Write that time down so you will know when you need to stop. For example, if you have 30 minutes and you are starting at 10:07, you will have to stop at 10:37. Now take half of the allowed time and figure that from the starting time. In our example, half of 30 minutes is 15 minutes, so write down 10:07 +0 :15 = 10:22. We’ll call this you half-time. By this time you will want to have at least looked at most of the problems.

When you find a problem that you have no clue about, circle its number on your list and go on. Continue through the problems, working the easy ones and marking the medium and impossible ones. Try to at least every problem read by half time.


As each problem is presented, decide if you know how to work it and can do it quickly. If so, then do it and enter your answer. If you think you can do it, but it will take some time, star its number on your list. You will want to come back to this one.

At half-time, if you have not finished looking at all the problems, continue as before, doing the easy ones, and marking the harder ones. When you have seen all the problems, start back and work on the starred, medium-difficulty ones. If you get all of these done and have time remaining, then try the circled, impossible ones. If there is a penalty for incorrect answers, you should not guess on these unless you can eliminate at least one of the choices. If you can rule out at least one choice, then it will be safe to guess. If there is no penalty for incorrect responses, then guess freely.

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Maths For Business Analytics


It is often said that good analytical decision-making has got very little to do with maths but a recent article in Towards Data Science pointed out that in the midst of the hype around data-driven decision making — the basics were somehow getting lost. The boom in data science requires an increase in executive statistics and maths skill.


While it is true that there is no better time to be in analytics than right now, business analysts should fulfil the basic requirements. Some of the fundamental concepts expected from a business analyst are correlation, causation and how to statistically test hypothesis. So, how well do business analysts know maths? Given that the primary language for business analysts is numbers, more attention should be paid to maths — the building block for their career. In terms of maths proficiency, business analysts are expected to have basic prerequisites in understanding how to manipulate basic algebraic expressions and the ability to solve equations. This also requires getting an understanding of how to graph different types of functions.


Tech entrepreneur Scott Brinker says that analytics teams are mushrooming everywhere across enterprises — from marketing analytics, HR analytics, predictive analytics to web analytics — and collectively they combine to form enterprise analytics. The rise of data and analytics skills has changed the way businesses function and every data savvy user is being equipped with self-service tools. However, their efficiency in getting into the depth of the model or understanding the logic behind the numbers thrown up is still questionable.



The Number Game



Of late, there has been a spate in the articles about how one can break into the field without the knowledge of heavy maths. This may be partially true, but for a strong foundation, persons without a maths background should identify areas that require beefing up such as linear algebra, calculus, probability, statistics, discrete mathematics, regression and optimisation, among others.


Keith McNulty, a well-known psychometrician and global director of People Analytics and Measurement at McKinsey, says that there are a few must-have basic concepts every analyst should know. For example, what does correlation mean and how to measure correlation coefficients for different types of data:



  • What does causation mean, how it is different from correlation, and how to prove causation
  • How to statistically test a hypothesis and the statistical conditions underlying hypothesis testing



Why Maths Is Crucial


According to a recent report, there is an acute shortage of persons with a science, technology, engineering and maths (STEM) background in India. The talent gap has risen from 6 percent in 2014 to 12 percent in 2018. As the demand for STEM occupations grows outside the traditional industries like IT and financial services to healthcare, marketing and other domains, there is an acute mismatch in talent.


According to Indeed’s survey findings, India produces the highest number of graduates with 78 million fresh graduates in 2016 alone, out of which 2.6 million took STEM courses. Despite the numbers, India faces a talent mismatch as the curriculum is not aligned with industry needs. Reports also suggest that job seekers, mostly fresh graduates, show a higher inclination for STEM jobs. In addition to this, findings from a recent Harvard study indicates that maths would be the most in-demand skill for the future workforce, which means that job roles will heavily weigh towards positions that require maths and logic proficiency.


Karl Kempf, chief mathematician at Intel and an Intel Fellow had once famously remarked, “If you want to be good about analytical decision-making, it’s not about the maths.” However, the famous mathematician, better known for money-saving attributes, believes that improving predictive models is of no use since forecasting is the “hardest problem in maths”.



Conclusion


Neither young candidates, nor working professionals can excel in analytics without having the required background in calculus and statistics. Hiring experts cite that a lack of coding experience can be bridged with training programs, but maths and logic are required to go behind the numbers. Hence, business analysts are expected to level up on key prerequisites such as probability, permutations and combinations, statistics — all of which are required to understand basic distribution, hypothesis testing, regressions, among others.



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