How to Complete Statistics Assignments on Time to Score Higher Grades?

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Statistics is not mathematics. Statistics is not just calculation. Statistics is the science of studying data and numbers.

It is the accumulation of quantitative data; and analysis, interpretation, classification, formulation, review of the same. Let’s say data is your institute and numbers are your textbooks.

You are to delve into the ocean of numbers and come out as an efficient Statistician. Your eye for numbers will come into play. But what it takes to score like a pro in Statisticsis a methodical and systematic approach in your study.

7 techniques to study your Statistics lessons better:

More than extensive hours of studying, Statistics requires a programmed study of chapters. Incorporate these 7 strategies in your study methods, and you are good to go.

  1. Perceive. Do not mug up:

Statistics is one subject you cannot master by simply memorising your chapters. The subject is entirely conceptual. Students often tend to mug up everything written in the textbooks. But here’s what. Mugging up does not work in Statistics.

After all, Statistics is an assimilation of concepts. How is one supposed to memorize concepts? So, drop that plan. The better you understand, the higher you score.

  • Teach a novice:

Do you know that teaching helps the teacher learn as well? It makes him/her well-versed with the chapter. Apply this technique.

Try explaining your chapters to someone who hasn’t studied it yet. Thismethod will help you have a lucid understanding of the chapter.

  • Group studies:

Studying in groups is more important than you realize. It addresses issues that do not arise from self-study. Interchange of ideas helps you have a better understanding of concepts.

Your classmates ask questions to clarify their doubts. Now, let’s say, you could have the same doubts eventually. But now you are immune from them beforehand.

  • Study your mood patterns:

There will be times a chapter seems too boring for you. Try switching. Open a different chapter and start studying.

The new chapter will come to you as a breath of fresh air. Even if this chapter is comparatively tougher, your brain will be more than happy to grasp it.

Say, you have been studying Probability since morning, and now you are drowsy. Instead of pushing your brain, try giving it something new. For instance, go over to Linear Programming. Switching will bring to you the refreshment you need.

  • Deduce your problem areas:

There will be certain chapters you don’t tend to get a grip of. Ignoring them is not an option. List them down and choose a time when you want to come back to them.

These are the chapters that require special attention. Get them figured out and plan on how to approach them.

  • Explore more:

Instead of working on problems from one chapter, try and solve problems from different chapters. This way, you have more say on the syllabus.

You might tend to stick to one chapter, as the thought of going on to the next one bores you. But to score high, learn to overcome this procrastination.

  • Immediate action:

Get your doubts cleared at the earliest hour. You start piling up your questions, and one day, it is too late.

Once new chapters keep coming in, going back to square one is not feasible. It becomes tough to grasp the new chapters as well.

If you aspire to be a high scorer in Statistics, lags should be a no-no.

3 tricks to calculate your data efficiently:

Always keep in mind that efficiency in estimating data is the number one priority. Statistics and efficiency go hand in hand.

  1. Concentration is the key:

Focus, focus and focus! A slight distraction and you lose your track. Let that not happen.

Speed breakers are not welcome while you are solving/calculating data. Numbers won’t wait for you. Stay hooked to your chapter. Study with perseverance.

  • No place for silly mistakes:

Try and cut on your basic errors. A minute mistake will lead to the whole data being erroneous. The entire data does not count if it is wrong. So, concent

Keep your additions, subtractions, divisions, multiplications apt, and everything else will fall in place.

  • Save time for verification:

Your assessment of a data will only count if it is correct, right? So ensure that you recheck after figuring out the data.

This will test your time managing skills as well. It is your task to bifurcate the stipulated time into:

  1. Estimation of data
  2. Monitoring the data

Why let others point out your mistakes when you can do it yourself?

How to bring faster outputs in Statistics?

Along with efficiency, speed comes into play as well. As a student of Statistics, you are expected to manage your time efficiently as well.

  1. Eye on the watch:

Keep track of how much time you are taking in which chapter. Certain chapters will need you to devote more time. These chapters are those that you find difficult or are comparatively lengthy.

Get these chapters classified and assort time to them accordingly. Don’t tend to devote more time on chapters you find easy or enjoy studying. Set your schedule, align the chapters with time and study accordingly.

  • Short-cuts in the calculations:

You need to find ways to shrink the calculation process. The faster you estimate, the more time you save for verification later on. There are certain tactics which are helpful to shorten the additions, subtractions, divisions and multiplications. You can learn those and utilize hem in your calculations.

But what comes like a warning bell here, is:

  1. Use those short-cuts only when you are a pro.
  2. Only if you the short-cuts lead to accurate results.
  • Don’t rush into things:

In data estimation, overspeeding is not fine. Once you have your task assigned, you might have this urge to get it done as fast as possible.

Although the intention is fine, you must start at a proper pace instead of dashing into it straight away. Rushing into the calculations will lead to erroneous outputs.

  • Regular practice:

You can master the art of accuracy only through practice. With thorough practice, you learn the tit-bits of how to be precise to the point.

A lag in practice does not work in Statistics. Skipping practice will only lead you to deep waters.

Briefing of the syllabus in Statistics course:

Part A: Statistics

  • Introduction to Statistics:

The chapter gives a brief about Statistics, its type and the scientific aspect of it.The latter part teaches the various steps included in Statistics-

  1. Collection
  2. Tabulation
  3. Statistical Inference

Frequency distribution of data: Proper observation and experiments of data. Studying the trends in the figures and arranging them accordingly.

Graphical Representation of Statistics: A smooth transition of numbers into graphs.

  • Measures of location:

Arithmetic mean, geometric mean, harmonic mean, knowledge of median, a lesson on mode, quartile dectile and percentile formula.

  • Measures of dispersion:

Definition of dispersion, standard deviation, mean deviation and quartile deviation.

  • Measures of Skewness and Kurtosis:

Concept of both Skewness and Kurtosis, along with ‘Moments’.

  • Correlation and Regression:

Correlation (determining the association between 2 variables) and Regression (determining the association between an independent variable and the dependant variable).

  • Probability:

Evaluating the chances of an event to occur again.

  • Probability distributions:

Linking each of the statistical data with its probability to occur again.

  • Sampling theory:

The process of selecting an individual observation to infer and analyse data from a group or collection.

  • Estimation of parameters:

The process of determining the parameters of a distribution from the given data.

  • Testing of Hypothesis:

Testing the probability of a given hypothesis with the use of statistics.

  • Analysis of Variance:

Better known as ANOVA, Analysis of Variance is the method of testing the differences between 2 means.

  • Stochastic Process:

Collecting random variables denoted byindex ‘t’, usually representing time.

Part B: Operations Research

  • Linear Programming:

This is also known as Linear Optimization. Linear programming is the noting downof different inequalities in a situation.

It is the method of considering different inequalities relevant to a situation. The best value is then calculated out of it, which is required to be obtained in those conditions.

  • Transportation Problems:

It is one type of Linear Programming. The idea is to minimize the cost of distribution while transporting a product from its sources to the final stop.

  • Assignment Problems:

This too comes under Linear Programming. It is the mechanism of allocating various resources to appropriate activities accordingly, in a way to:

  1. Minimize the cost of production and
  2. Maximize profit.
  • Queuing Theory:

It is the mathematical study of queuing. When customers come to a shop, they might have to wait in a line to purchase/avail the products or services. Queuing theory is the analysis and examining of all components in a queue.

  • Inventory Control:

Also known as ‘stock control’. It is the method of studying the stock available with a seller. This is done to minimize the total cost of inventory of the shop.

  • Simulation:

This is the process of drawing artificially generated data to test a new statistical method or a hypothesis.

The random data used in suchtests are called stimulated data.

Network Scheduling by CPM/IPERT:

Both CPM (Critical Part Method) and IPERT (Innovative Programs to Enhance Research Training) are used in project management.

  • Network Scheduling is the sequencing of processes involved in project management. It ensures proper estimation of time and cost in the project.
  • Game Theory:

It is the process of framing the interaction between two or more participants in an activity.

  • It helps to determine the likely outcomes from the interaction between two or more firms.

What skills does Statistics teach you?

Every subject has certain values to teach you. These values go beyond academics. Statistics too has these 5 invaluable lessons to teach you that you can engulf in day to day life.

  1. Time management:

While dealing with statistics and data, you eventually learn how to master the art of managing time.

How much time to alott to a particular work, how to schedule your day, how to make most of your time; a student of Statistics has a better answer to these questions. After all, we all have only 24 hours in a day.

  • Better judgement skills:

Statistics teaches you not to jump into conclusions. You are supposed to analyze data and then have an impression about it.

Implementing this in your day to day life will make you a better and wiser person. You don’t rush to conclusions. You watch, perceive, analyse and then judge situations and people.

  • A better connection with your surroundings:

Dealing with data will make you more aware of things around you.

You get enlightened with a lot of facts and knowledge.

  • Precision:

Statistics teaches you the value of precision in a task. If you are doing something, but not doing it with the effort it needs, your work doesn’t count at all.

Accuracy is what makes you better than the rest.

  • Patience:

Collecting, estimating and analysis data need utter patience. You can’t afford to get restless. Your mind has to work in peace.

The student has to be patient enough to execute the actions properly. Perfect coherence of patience and concentration will lead to accurate statistical operations. Thus, it teaches you to be calm and patient in day to day life.

The world runs with Statistics today. Everything has to be under proper vigilance. Statistical data act like a vigil on every activity, every transaction, every trend, every situation in and around the world.

Statistics is the present, and it is the future. As a statistician, you assess the present and draw insightinto the future. In a way, Statistics is the intermediate between an action and a reaction.

About the author:

MajaKazazic, a researchist in a Research and Development program in the US government, holds a Master degree in Statistics from the University of Chicago.He is known to assist students of Statistics with their projects and assignments. He looks to make Statistics an interesting subject for students to help them learn and explore more.