JBDON
  • Home
  • Applied Analytics
    • Analytics for Decision Making >
      • What is Cluster Analysis
      • Data Reduction and Unsupervised Learning
      • Preparing Data and Measuring Dissimilarities
      • Hierarchical and k-Means Clustering
      • Defining Output Variables and Analyzing the Results
      • Using Historical Data to Model Uncertainty
      • Models with Correlated Uncertain Variables
      • Creating and Interpreting Charts
      • Using Average Values versus Simulation
      • Optimization and Decision Making
      • Formulating an Optimization Problem
      • Developing a Spreadsheet Model
      • Adding Optimization to a Spreadsheet Model
      • What-if Analysis and the Sensitivity Report
      • Evaluating Scenarios and Visualizing Results to Gain Practical Insights
      • Digital Marketing Application of Optimization
      • Advanced Models for Better Decisions
      • Business Problems with Yes/No Decisions
      • Formulation and Solution of Binary Optimization Problems
      • Metaheuristic Optimization
      • Chance Constraints and Value At Risk
      • Simulation Optimization
    • Analytics for Marketing >
      • Marketing Analytics and Customer Satisfaction
      • Customer Satisfaction
      • Measurements and Scaling Techniques – Introduction
      • Primary Scales of Measurement
      • Comparative Scaling
      • Non-Comparative Scaling
      • Experiment Design: Controlling for Experimental Errors
      • A/B Testing: Introduction
      • A/B Testing: Types of Tests
      • ANOVA – Introduction
      • Example -Inspect Spray and Tooth Growth
      • Logit Model - Binary Outome and Forecastign linear regression
      • Text Summarization
      • Social media Microscope
      • N-Gram - Frequcy Count and phase mining
      • LDA Topic Modeling
      • Machine-Learned Classification and Semantic Topic Tagging
    • Data Engine >
      • Understanding The Growth Of Data
      • Evaluating Methods Of Data Access
      • Communication journey
      • Data Journey
      • Planning for data visualisation
      • Visualisation Component
      • Content Connection and Chart Legitibility
    • Customer Insights >
      • Introduction
      • What is Descriptive Analytics?
      • Survey Overview
      • Net Promoter Score and Self-Reports
      • Survey Design
      • Passive Data Collection
      • Media Planning
      • Data Visualization
      • Causal Data Collection and Summary
      • Asking Predictive Questions
      • Regression Analysis
      • Data Set Predictions
      • Probability Models
      • Results and Predictions
      • Perspective Analytics (Maximize Revenue and Market Structure Competitions)
    • Analytics for Advance Marketing >
      • Visualisation and statistics (Political Advertising,Movie Theater and Data Assembly)
      • Excel Analysis of Motion Picture Industry Data
      • Displaying Conditional Distributions
      • Analyzing Qualitative Variables
      • Steps in Constructing Histograms
      • Common Descriptive Statistics for Quantitative Data
      • Regression-Based Modeling
      • Customer Analytics
      • Illustrating Customer Analytics in Excel
      • Customer Valuation Excel Demonstration
  • Soft Skills
    • Adaptability
    • Confidence
    • Change Management
    • Unlearning and Learning
    • Collaboration and Teamwork
    • Cultural Sensitivity
  • Marketing
  • Finance
  • Economics
    • Introduction to Managerial Economics >
      • Basic Techniques
      • The firm: Stakeholders, Objectives and Decision Issues
      • Demand and Revenue Analysis >
        • Demand Estimation and Forecasting
        • Demand Elasticity
        • Demand Concepts and Analysis >
          • Formulation and Solution of Binary Optimization Problems
      • Scope of Managerial Economics
    • Prodution and Cost Analysis >
      • Production Function
      • Estimation of Production and Cost Functions
      • Cost Concepts and Analysis I
      • Cost Concepts and Analysis II
    • Pricing Decisions >
      • Pricing strategies >
        • Adding Optimization to a Spreadsheet Model
      • Market structure and microbes barriers to entry
      • Pricing under pure competition and pure monopoly
      • Pricing under monopolistic and oligopolistic competition
    • Narendra Modi Development Model of Gujarat
  • JBDON Golf
    • Digital Marketing Application of Optimization
  • Let's Talk
  • MBA Project Sharing
  • About Us
    • Good Read >
      • IIMC says PepsiCo CEO Indra Nooyi was an average student
      • India’s middle class figures in Fortune’s Top Ten list of those who matter
      • The Start-Up of you.
      • BUYING AND MERCHANDISING
      • HUMAN RESOURCE MANAGEMENT
      • Do You Suffer From Decision Fatigue?
      • New Page
      • About social media and web 2.0
      • Building Your Own Start-up Technology Company, Part 1
      • Building Your Own Start-up Technology Company, Part 2
      • Building Your Own Start-up Technology Company, Part 3
      • Building Your Own Start-up Technology Company, Part 4
      • Renewable energy is no longer alternative energy
      • What Makes an Exceptional Social Media Manager?
      • The Forgotten Book that Helped Shape the Modern Economy
      • Home
      • How to Think Creatively
      • A Lighthearted Looks at Project Management and Sports Analogies
      • Why Trust Matters More Than Ever for Brands
  • CET Knowledge Zone
    • Tips From JBIMS Students >
      • Prasad Sawant
      • Chandan Roy
      • Ram
      • Ashmant Tiwari
      • Rajesh Rikame
      • Ami Kothari
      • Ankeet Adani
      • Sonam Jain
      • Marketing Analytics and Customer Satisfaction
      • Mitesh Thakker
      • Tresa Sankoorikal
    • Speed Techniques
    • CET Workshops
  • Untitled
  • New Page
    • Cluster analysis using excel and excel miner
    • Chance Constraints and Value At Risk
    • Adding Uncertainty to a Spreadsheet Model
  • Adidas

Prasad Sawant, JBIMS Batch of 2011

Picture
I think this is the ideal time to wish aspirants all the best and to talk about things that aspirants should take care of

(Again my views, you may or may not agree)

1. Enough of what we call traditional preparation. I think one should not try to learn something new at this stage. If you dont know permutation and combination completely...leave it. If you know permutation and combination. but dont know it very well, solve few sums and go through concepts. Its like if I divide all sections in four regions

strength area - You need to crack this left right in the exam.
fairly good area - You need to crack this with more than 80% accuracy
weakness area - more than 60% accuracy
(I dont know anything about this) area - keep these questions to solve at the end.

This is not the time to solve mocks also. I personally wont suggest taking mock after Friday. See to it that you go through basic concepts, solved mocks, and important questions again. Your past mock scores were indicator of your performance at a particular level. CET 10 may or many not test that. Irrespective of difficulty level, aim should be to overtake all earlier performances.

2. Strategy - differs from person to person. and I dont think I have the right to tell you a particular strategy now. Those who have solved n number of mocks are already aware of what to do in the paper. My suggestion - A strategy MIGHT fail in the exam due to number of questions or the sequence in which those questions are asked. To avoid any issues Have a backup strategy.

3. Speed - Think of CET as the most important 2.5 hours of your life. You should get that sense of urgency once you get question paper. But dont get tensed. The time provided by dte is enough, it depends on how you use that time!

4. Number of questions, cutoffs and what not - There is nothing like ideal attempts, as cutoffs depend on difficulty level of paper. Now what will you do in such case - solve maximum possible number of questions with maximum possible accuracy. dont think of results or cutoffs. If paper is difficult, it will be difficult for everyone. You will realize the public perception only when you are out of exam hall. When you are inside, solve maximum possible number of questions with maximum possible accuracy

please mark on OMR properly and take care of OMR.

5. Saturday and Sunday

On Saturday, solve few sums here and there, read concepts, tables, formulae etc. and relax. Sleep well too.

On Sunday, Pray

Before leaving for the exam, have a checklist which should ideally involve
(indicative not exhaustive)

- 2 printouts of your application
- 2 printouts of your hall ticket
- watch
- water bottle
- some identity proof
- black ball pens (2-3). carry pencils also.
- whatever they have asked on hall ticket

Please reach at the venue half an hour early. GO with your parents or with someone close to you. {if you have time now, go and have a look at your exam venue}.

Nothing more from my side. CET is you against yourself. Dont think of the number of candidates. You need to win yourself. Take this as an opportunity to show your caliber.

A day before exam, I was also tensed. Its part and parcel of the game. keep your calm in those 2.5 hours. If you have worked hard before and do well in those 2.5 hours, I am sure you will end up winning.

-----------------------


A Little More...

1. Mocks and study material

I don't understand the logic behind taking 2 mocks a day. In the process one is actually hampering his/her performance. Stick to a mock a day or a mock on alternate day (depending on number of mocks you have solved before and the amount of preparation that you have put in so far).

If you have solved a lot of mocks before (say 20) you can start with a mock on alternate days. On the remaining days, you need to solve whatever study material you have (includes going through previous mocks and coaching insti study material etc.)

If you havent taken mocks before, start a mock a day. Remember, you also need to study material along with this. Put in those extra efforts.

One suggestion about mocks. Take mocks in afternoon 2 to 4.30 slot if possible. See to it that you are using a black ball point pen and taking mock as actual CET apper.

2. Preparation part

There are people who have started their preparation late or are not having their concepts in place. the only suggestion is start solving. Take books from whichever source (beg, borrow, steal). Start solving coaching insti material. daily 200-300 questions depending on your ability to digest it. See your strengths and weaknesses. Utilize next few days in building upon your strengths and improving your weaknesses.

One can sit for 10 hours and do nothing while one can sit for 2 hours and do everything. Hope you are getting what I am trying to say. Focus on quality.

3. Seriousness

the typical problem is I am solving mocks. but nothing is coming out of it. My question is are you giving 100%? Are you taking it as a do or die situation? Are you analyzing these mocks well? Are you planning strategies for this battle? If answer is NO. that means you are not serious and its better if you realize this early. Its important to be serious at this stage. This is sincere request from my side.

4. Hope and faith

Can I do it? what if I cant? What if I give 100% and dont get it? Dont think about these questions. Those who are telling you that this can not be done are mad. dont listen to them. I am not bothered with you being a fresher, a 5 yr work ex or a 10 year work ex guy. I am not bothered whether you are B.Sc./ B.Com./CA/doctor or engineer. people from all backgrounds have done it in the past. So dont worry about this. you can do it and this is the time when you should do it.

You will find sudden increase in no. of people giving you gyan on how to crack CET. I am not saying I am right or do as I say. Listen to everyone, but do what is right for you. Every individual is different. If solving a mock a day is not suitable for u, dont do it. do something productive instead. Visit coaching institutes if you have enrolled. spend time with faculty. chew their brains and get your doubts solved. you have paid money, make good use of it.

Believe in yourself. prove that you have that spirit.



Last suggestion - please be serious with the application forms. Fill the details well. Dont play with it. results have been disastrous in the past. Fill it well before time to avoid last minute problems. read brochure carefully.

All the best to all aspirants!

Powered by Create your own unique website with customizable templates.
  • Home
  • Applied Analytics
    • Analytics for Decision Making >
      • What is Cluster Analysis
      • Data Reduction and Unsupervised Learning
      • Preparing Data and Measuring Dissimilarities
      • Hierarchical and k-Means Clustering
      • Defining Output Variables and Analyzing the Results
      • Using Historical Data to Model Uncertainty
      • Models with Correlated Uncertain Variables
      • Creating and Interpreting Charts
      • Using Average Values versus Simulation
      • Optimization and Decision Making
      • Formulating an Optimization Problem
      • Developing a Spreadsheet Model
      • Adding Optimization to a Spreadsheet Model
      • What-if Analysis and the Sensitivity Report
      • Evaluating Scenarios and Visualizing Results to Gain Practical Insights
      • Digital Marketing Application of Optimization
      • Advanced Models for Better Decisions
      • Business Problems with Yes/No Decisions
      • Formulation and Solution of Binary Optimization Problems
      • Metaheuristic Optimization
      • Chance Constraints and Value At Risk
      • Simulation Optimization
    • Analytics for Marketing >
      • Marketing Analytics and Customer Satisfaction
      • Customer Satisfaction
      • Measurements and Scaling Techniques – Introduction
      • Primary Scales of Measurement
      • Comparative Scaling
      • Non-Comparative Scaling
      • Experiment Design: Controlling for Experimental Errors
      • A/B Testing: Introduction
      • A/B Testing: Types of Tests
      • ANOVA – Introduction
      • Example -Inspect Spray and Tooth Growth
      • Logit Model - Binary Outome and Forecastign linear regression
      • Text Summarization
      • Social media Microscope
      • N-Gram - Frequcy Count and phase mining
      • LDA Topic Modeling
      • Machine-Learned Classification and Semantic Topic Tagging
    • Data Engine >
      • Understanding The Growth Of Data
      • Evaluating Methods Of Data Access
      • Communication journey
      • Data Journey
      • Planning for data visualisation
      • Visualisation Component
      • Content Connection and Chart Legitibility
    • Customer Insights >
      • Introduction
      • What is Descriptive Analytics?
      • Survey Overview
      • Net Promoter Score and Self-Reports
      • Survey Design
      • Passive Data Collection
      • Media Planning
      • Data Visualization
      • Causal Data Collection and Summary
      • Asking Predictive Questions
      • Regression Analysis
      • Data Set Predictions
      • Probability Models
      • Results and Predictions
      • Perspective Analytics (Maximize Revenue and Market Structure Competitions)
    • Analytics for Advance Marketing >
      • Visualisation and statistics (Political Advertising,Movie Theater and Data Assembly)
      • Excel Analysis of Motion Picture Industry Data
      • Displaying Conditional Distributions
      • Analyzing Qualitative Variables
      • Steps in Constructing Histograms
      • Common Descriptive Statistics for Quantitative Data
      • Regression-Based Modeling
      • Customer Analytics
      • Illustrating Customer Analytics in Excel
      • Customer Valuation Excel Demonstration
  • Soft Skills
    • Adaptability
    • Confidence
    • Change Management
    • Unlearning and Learning
    • Collaboration and Teamwork
    • Cultural Sensitivity
  • Marketing
  • Finance
  • Economics
    • Introduction to Managerial Economics >
      • Basic Techniques
      • The firm: Stakeholders, Objectives and Decision Issues
      • Demand and Revenue Analysis >
        • Demand Estimation and Forecasting
        • Demand Elasticity
        • Demand Concepts and Analysis >
          • Formulation and Solution of Binary Optimization Problems
      • Scope of Managerial Economics
    • Prodution and Cost Analysis >
      • Production Function
      • Estimation of Production and Cost Functions
      • Cost Concepts and Analysis I
      • Cost Concepts and Analysis II
    • Pricing Decisions >
      • Pricing strategies >
        • Adding Optimization to a Spreadsheet Model
      • Market structure and microbes barriers to entry
      • Pricing under pure competition and pure monopoly
      • Pricing under monopolistic and oligopolistic competition
    • Narendra Modi Development Model of Gujarat
  • JBDON Golf
    • Digital Marketing Application of Optimization
  • Let's Talk
  • MBA Project Sharing
  • About Us
    • Good Read >
      • IIMC says PepsiCo CEO Indra Nooyi was an average student
      • India’s middle class figures in Fortune’s Top Ten list of those who matter
      • The Start-Up of you.
      • BUYING AND MERCHANDISING
      • HUMAN RESOURCE MANAGEMENT
      • Do You Suffer From Decision Fatigue?
      • New Page
      • About social media and web 2.0
      • Building Your Own Start-up Technology Company, Part 1
      • Building Your Own Start-up Technology Company, Part 2
      • Building Your Own Start-up Technology Company, Part 3
      • Building Your Own Start-up Technology Company, Part 4
      • Renewable energy is no longer alternative energy
      • What Makes an Exceptional Social Media Manager?
      • The Forgotten Book that Helped Shape the Modern Economy
      • Home
      • How to Think Creatively
      • A Lighthearted Looks at Project Management and Sports Analogies
      • Why Trust Matters More Than Ever for Brands
  • CET Knowledge Zone
    • Tips From JBIMS Students >
      • Prasad Sawant
      • Chandan Roy
      • Ram
      • Ashmant Tiwari
      • Rajesh Rikame
      • Ami Kothari
      • Ankeet Adani
      • Sonam Jain
      • Marketing Analytics and Customer Satisfaction
      • Mitesh Thakker
      • Tresa Sankoorikal
    • Speed Techniques
    • CET Workshops
  • Untitled
  • New Page
    • Cluster analysis using excel and excel miner
    • Chance Constraints and Value At Risk
    • Adding Uncertainty to a Spreadsheet Model
  • Adidas