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DIPLOMA IN QUANTITATIVE TECHNIQUES IN BUSINESS

Rs.2,500.00 Rs.1,250.00

Diploma in Quantitative Techniques for Management.

Learn how to make a powerful decision in a systematic and powerful means of analysis, based on quantitative data.

Explore the policies for attaining the predetermined objectives.

Decision making Analysis is taught during the course which will be an added advantage.

Description

Course Name: DIPLOMA IN QUANTITATIVE TECHNIQUES IN BUSINESS
Course Id: DQTB/Q1001.
Education Qualification: 12th Pass.
Course and Exam Fee: 2500.

How You will Get Diploma Certificate:

Step 1- Select your Course for Certification.

Step 2- Click on Enroll Now.

Step 3- Proceed to Enroll Now.

Step 4- Fill Your Billing Details and Proceed to Pay.

Step 5- You Will be Redirected to Payment Gateway, Pay Course and Exam Fee by Following Options.

Card(Debit/Credit), Wallet, Paytm, Net banking, UPI and Google pay.

Step 6- After Payment You will receive Study Material and Online Examination link on your email id.

Step 7- After Completion of  Course Study give Online Examination.

Step 8- After Online Examination within 7 days you will get Diploma Certificate soft copy(Scan Copy) and Hard Copy(Original With Seal and Sign) within 30 days.

Step 9- After Certification you will receive Prospect Job Opportunities as per your Interest Area.

Online Examination Detail:

Duration- 60 minutes.

No. of Questions- 30. (Multiple choice Questions).

Maximum Marks- 600, Passing Marks- 40%.

There is No Negative marking in this module.

Benefits of Certification:

  • Government Authorized Assessment Agency Certification.
  • Certificate Valid for Lifetime.
  • Lifetime Verification of Certificate.
  • Free Job Assistance as per your Interest Area.

Or You Can Fill below Enquiry form For Regular Course Training from our Training Centers located in India.

Student Course Enquiry Form:

SYLLABUS

 

DIPLOMA IN QUANTITATIVE TECHNIQUES IN BUSINESS
Name of PaperM. MarksPass Marks
Introduction to quantitative techniques10040
Correlation and Regression10040
Probability and probability distributions10040
Time Series and Index Number10040
Sampling10040
Uni-Variate Data Analysis10040
Practical10040

 

Introduction to quantitative techniques

To familiarize student with the use quantitative techniques in managerial decision making, On completing the course students will be able to Understand and develop insights and knowledge base of various concepts of Quantitative Techniques, Develop skills for effectively analyze and apply Quantitative Techniques in decision making, Quantitative Techniques: Introduction – Meaning and Definition – Classification of QT -QT and other disciplines – Application of QT in business – Limitations, Quantitative Techniques, Measures of Central Tendency,  Mathematical Model, Linear Programming: Graphical Method, Linear Programming: Simplex Method, Meaning of quantitative techniques, Development of quantitative techniques, areas where quantitative techniques are applicable, Role of quantitative techniques, Types of quantitative techniques.

Correlation and Regression

Correlation and Regression Analysis: Correlation:- Meaning, significance and types; Methods of Simple correlation – Karl Pearson‟s coefficient of correlation, Spearman‟s Rank correlation – Regression -Meaning and significance; Regression vs. Correlation – Linear Regression, Regression lines (X on Y, Y on X) and Standard error of estimate. Definition of terms: correlation and regression, Differences and similarities between correlation and regression, Methods of studying correlation, Interpretation of correlation coefficient, linear regression equation, Forecasting using regression equation.

Probability and probability distributions

Probability: –Concept of Probability—Meaning and Definition— Approaches to Probability Theorems of Probability—Addition Theorem— Multiplication Theorem—Conditional Probability—Inverse Probability—Bayes’ Theorem – Sets Theory: Meaning of Set – Set Operation – Venn Diagrams, Ddefinition of basic terms used in probability, Basic concepts of probability, Laws of probability, Probability distributions, Application of basic probability distribution functions, Concept of Probability, Meaning and Definition, Approaches to Probability Theorems of Probability, Addition Theorem ,Multiplication Theorem, Conditional Probability, Inverse Probability, Bayes’ Theorem, Sets Theory: Meaning of Set, Set Operation, Venn Diagrams.

Time Series and Index Number

Time Series and Index Number: Meaning and Significance – Utility, Components of Time Series- Measurement of Trend: Method of Least Squares, Parabolic Trend and Logarithmic Trend- Index Numbers: Meaning and Significance, Problems in Construction of Index Numbers, Methods of Constructing Index Numbers – Weighted and Un weighted, Test of Adequacy of Index Numbers, Chain Index Numbers, Uses of index numbers, Types of index numbers, Factors to be considered in construction of index numbers, Problems encountered when constructing index numbers, Computation of index numbers, Limitation of index numbers. Difference between frequency and probability distributions, Binomial, Poisson and normal distribution Note: Relevant Case Studies should be discussed in class.

Sampling

Concept and definitions, census and sampling, probability samples and non-probability samples, relationship between sample size and errors, simple numerical only. Hypothesis Testing: Sampling theory; Formulation of Hypotheses; Application of Z-test, t-test, F-test and Chi-Square test, techniques of association of attributes & testing. Test of significance for small sample, Types of Sampling methods, Census method and Sampling – Difference between census and sampling -Theoretical base of sampling, Non-Probability Sampling Types, Convenience Sampling, Consecutive Sampling, Quota Sampling, Snowball Sampling, Purposive or Judgmental Sampling, What are the methods of probability sampling.

Uni-Variate Data Analysis

Measures of Central Tendency – Concept – Functions of an average- Characteristics- Arithmetic Mean –Simple mean Weighted mean- Combined mean- Properties of mean- Median –Quartiles and other partition values- Mode- Empirical relation between mean, median and mode- Graphical location of median and mode- Geometric Mean- Harmonic Mean-relation between Arithmetic mean, Geometric mean and Harmonic Mean Application of various measures- Merits and Demerits of various measures of central tendency, Measures of dispersion – Concept-Properties of a good measure of dispersion- Absolute and Relative Measure-Range-Inter Quartile Range- Quartile Deviation.