DIPS ACADEMY has truly been one of the most profound learning experience where I gained the confidence to move ahead in my carrer with the opportunity to put myself on the forefront in dealing mathematics. DIPS programme is very well designed with very helpful test series. Dubey Sir and other faculty are superb. The lectures of Dubey Sir are the most intersting and inspiring.
I am very contented with the dips family specially dubey sir, he's an excellent mentor with amazing teaching skills.The mathematical atmosphere along with one to one interaction, dips material and doubt clearing sessions provided by DIPS ACADEMY were very helpful throughout the journey.
" The guidance of Dubey Sir, a teacher with immense knowledge and wonderful teaching skills, was of great help for me. His approach towards tackling problems, in particular, is pecular and worth emulating I thank him for his invaluable guidance and continuous motivation. "
I'm Mamta Kumari and I secured AIR 47 in IIT - JAM Mathematics. I am very thankful to Dubey Sir, Amit Sir and all the other faculty members for their teachings and guidance. The classes used to be very interactive and environment was very positive for learning. I have learned a lot from Dips academy and I'm very thankful to all the faculties for teaching us the actual meaning of Mathematics in the best possible way.
Dips Academy also has test series for IIT Jam Statistics aspirants which are designed by industry leaders. They designed the test series in such a way that you not only practice questions with our test series, but we also assist you, “how to crack the exam”.
Our test series is available online so that you have the freedom to conduct the test as per your own comfort and timings. Our 360 degree analysis which is performed online on the basis of your performance will assist you in the preparation of the competitive exams and scale your performance among the competitive students all across the nation.
The result of each exam will be declared on the next day of the exam (in the morning session) and will be available for next two days on your panel with full analysis of exams and your performance in the exams. Our online test series are not identical to regular student but it is merged with test series, which are acquired by our regular students of our academy.
In this way you can compete with the most serious and generic aspirants which are lacking in other test series available in the market. Hence, students have the facility to check their knowledge among the most competitive environment before the actual exam.
Standard Quality Questions
Questions are placed as per the weight age of the question in the exam
Availability of question on each concept
Practicing these questions can help you in understanding the whole concept.
Topic or concept wise test and Full length test available.
Get Answer and solution post test
Analysis of your performance
Availability of similar pattern as per the exam
Attempt the exam as per your norms.
(Online Test Series)
12 Test (8 Module Wise + 4 Full Length)
Rs. 1000 /- (+ GST)
IIT-JAM STATISTICS TEST SERIES SCHEDULE 2025 |
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| TEST TYPE | Modules | Date | Syllabus |
| MWT-01 | PROBABILITY AND DISTRIBUTION FUNCTION | 24-Dec-2024 | Probability: Random Experiments. Sample space and Algebra of Events (Event space). Relative frequency and Axiomatic definitons of probability. Properties of probability function. Addition theorem of probability fucntion (inclusion exclusion principle). Geometric probability. Boole's and Bonferroni's inequaliites. conditional probability and multiplication rule. theorem of total probability and Bayes' theorem. pairwise and mutual independence of events. Univariate Distributions: Definition of random variabels. cumulative distribution fucntion (cdf) of a random variable. Discrete and Continuous random variables. probability mass fucntion (pmf) and probability density fucnion (pdf) of a random variabel. Distribution (cdf, pmf, pdf) of a function of a random variable using transformation of variable and Jacobian method. mathematical expectation and moments. mean, median, mode, variance, standard deviation, Coefficient of variation, quantiles , quartiles, coefficient of variation, and measures of Skewness and Kurtosis of a probability distribution. moment generating function (mgf), its properties and uniqueness, markov and Chebyshev inequalities and their applications |
| MWT-02 | UNIVARIATE DISTRIBUTION+MULTIVARIATE DIS | 27-Dec-24 | Standard Univariate Distributions: Degenerate, Bernoulli, Binomial, Negative binomial, Geometric, Poisson, Hypergeometric, Uniform, Exponential, Double exponential, Gamma, Beta (of first and second type), Normal and Cauchy distributions, their properties, interrelations, and limiting (approximation) cases.Multivariate Distributions: Definition of random vectors. Joint and marginal c.d.f.s of a random vector. Discrete and continuous type random vectors. Joint and marginal p.m.f., joint and marginal p.d.f.. Conditional c.d.f., conditional p.m.f. and conditional p.d.f.. Independence of random variables. Distribution of functions of random vectors using transformation of variables and Jacobian method. Mathematical expectation of functions of random vectors. Joint moments, Covariance and Correlation. Joint moment generating function and its properties. Uniqueness of joint m.g.f. and its applications. Conditional moments, conditional expectations and conditional variance. Additive properties of Binomial, Poisson, Negative Binomial, Gamma and Normal Distributions using their m.g.f.. Standard Multivariate Distributions : Multinomial distribution as a generalization of binomial distribution and its properties (moments, correlation, marginal distributions, additive property). Bivariate normal distribution, its marginal and conditional distributions and related properties. |
| MWT-03 | REAL ANALYSIS | 31-Dec-24 | Sequences and Series of real numbers: Sequences of real numbers, their convergence, and limits. Cauchy sequences and their convergence. Monotonic sequences and their limits. Limits of standard sequences. Infinite series and its convergence, and divergence. Convergence of series with non-negative terms. Tests for convergence and divergence of a series. Comparison test, limit comparison test, D’Alembert’s ratio test, Cauchy’s 𝑛 𝑡 root test, Cauchy’s condensation test and integral test. Absolute convergence of series. Leibnitz’s test for the convergence of alternating series. Conditional convergence. Convergence of power series and radius of convergence. Differential Calculus of one and two real variables: Limits of functions of one real variable. Continuity and differentiability of functions of one real variable. Properties of continuous and differentiable functions of one real variable. Rolle's theorem and Lagrange's mean value theorems. Higher order derivatives, Lebnitz's rule and its applications. Taylor's theorem with Lagrange's and Cauchy's form of remainders. Taylor's and Maclaurin's series of standard functions. Indeterminate forms and L' Hospital's rule. Maxima and minima of functions of one real variable, critical points, local maxima and minima, global maxima and minima, and point of inflection. Limits of functions of two real variables. Continuity and differentiability of functions of two real variables. Properties of continuous and differentiable functions of two real variables. Partial differentiation and total differentiation. Lebnitz's rule for successive differentiation. Maxima and minima of functions of two real variables. Critical points, Hessian matrix, and saddle points. Constrained optimization techniques (with Lagrange multiplier). |
| MWT-04 | LIMIT THEOREM +SAMPLING DISTRIBUTION +REG | 04-Jan-25 | Limit Theorems: Convergence in probability, convergence in distribution and their inter relations. Weak law of large numbers and Central Limit Theorem (i.i.d. case) and their applications. Sampling Distributions: Definitions of random sample, parameter and statistic. Sampling distribution of a statistic. Order Statistics: Definition and distribution of the rth order statistic (d.f. and p.d.f. for i.i.d. case for continuous distributions). Distribution (c.d.f., p.m.f., p.d.f.) of smallest and largest order statistics (i.i.d. case for discrete as well as continuous distributions). Central Chisquare distribution: Definition and derivation of p.d.f. of central X2 distribution with n degrees of freedom (d.f.) using m.g.f.. Properties of central X2 distribution, additive property and limiting form of central X2 distribution. Central Student's t-distribution: Definition and derivation of p.d.f. of Central Student's t-distribution with n d.f., Properties and limiting form of central t-distribution. Snedecor's Central F-distribution: Definition and derivation of p.d.f. of Snedecor's Central F- distribution with (m,n ) d.f.. Properties of Central F-distribution, dist. Regression: Least squares estimation and its applications in simple linear regression models. |
| MWT-05 | LINEAR ALGEBRA | 08-Jan-25 | Linear algebra: Vector spaces with real field. Subspaces and sum of subspaces. Span of a set. Linear dependence and independence. Dimension and basis. Algebra of matrices. Standard matrices (Symmetric and Skew Symmetric matrices, Hermitian and Skew Hermitian matrices, Orthogonal and Unitary matrices, Idempotent and Nilpotent matrices). Definition, properties and applications of determinants. Evaluation of determinants using transformations. Determinant of product of matrices. Singular and non-singular matrices and their properties. Trace of a matrix. Adjoint and inverse of a matrix and related properties. Rank of a matrix, row-rank, column-rank, standard theorems on ranks, rank of the sum and the product of two matrices. Row reduction and echelon forms. Partitioning of matrices and simple properties. Consistent and inconsistent system of linear equations. Properties of solutions of system of linear equations. Use of determinants in solution to the system of linear equations. Cramer’s rule. Characteristic roots and Characteristic vectors. Properties of characteristic roots and vectors. Cayley Hamilton theorem |
| MWT-06 | ESTIMATION THEORY | 12-Jan-25 | Estimation: Unbiasedness. Sufficiency of a statistic. Factorization theorem. Complete statistic. Consistency and relative efficiency of estimators. Uniformly Minimum variance unbiased estimator (UMVUE). Rao-Blackwell and Lehmann-Scheffe theorems and their applications. Cramer-Rao inequality and UMVUEs. Methods of Estimation: Method of moments, method of maximum likelihood, invariance of maximum likelihood estimators. Confidence intervals and confidence coefficient. Confidence intervals for the parameters of univariate normal, two independent normal, and exponential distributions |
| MWT-07 | TESTING OF HYPOTHESIS | 14-Jan-25 | Testing of Hypotheses: Null and alternative hypotheses (simple and composite), Type-I and Type-II errors. Critical region. Level of significance, size and power of a test, p-value. Most powerful critical regions and most powerful (MP) tests. Uniformly most powerful (UMP) tests. Neyman Pearson Lemma (without proof) and its applications to construction of MP and UMP tests for parameter of single parameter parametric families. Likelihood ratio tests for parameters of univariate normal distribution. |
| MWT-08 | INTEGRAL CALCULUS | 18-Jan-25 | Integral Calculus: Fundamental theorems of integral calculus (single integral). Lebnitz's rule and its applications. Differentiation under integral sign. Improper integrals. Beta and Gamma integrals: properties and relationship between them. Double integrals. Change of order of integration. Transformation of variables. Applications of definite integrals. Arc lengths, areas and volumes |
| FLT-01 | Full Length Test | 20-Jan-25 | As per Exam Pattern |
| FLT-02 | Full Length Test | 23-Jan-25 | As per Exam Pattern |
| FLT-03 | Full Length Test | 26-Jan-25 | As per Exam Pattern |
| FLT-04 | Full Length Test | 28-Jan-25 | As per Exam Pattern |
DIPS ACADEMY has truly been one of the most profound learning experience where I gained the confidence to move ahead in my carrer with the opportunity to put myself on the forefront in dealing mathematics. DIPS programme is very well designed with very helpful test series. Dubey Sir and other faculty are superb. The lectures of Dubey Sir are the most intersting and inspiring.
I am very contented with the dips family specially dubey sir, he's an excellent mentor with amazing teaching skills.The mathematical atmosphere along with one to one interaction, dips material and doubt clearing sessions provided by DIPS ACADEMY were very helpful throughout the journey.
" The guidance of Dubey Sir, a teacher with immense knowledge and wonderful teaching skills, was of great help for me. His approach towards tackling problems, in particular, is pecular and worth emulating I thank him for his invaluable guidance and continuous motivation. "
I'm Mamta Kumari and I secured AIR 47 in IIT - JAM Mathematics. I am very thankful to Dubey Sir, Amit Sir and all the other faculty members for their teachings and guidance. The classes used to be very interactive and environment was very positive for learning. I have learned a lot from Dips academy and I'm very thankful to all the faculties for teaching us the actual meaning of Mathematics in the best possible way.
