The document discusses infinite series and their convergence. An infinite series is defined as the sum of the terms of an infinite sequence. For an infinite series to have meaning, the limit of the partial sums as they approach infinity must exist. If this limit converges, the series converges; if not, it diverges. Geometric series and integral tests are introduced as methods to determine convergence. Examples are provided to demonstrate applying these tests.
This document contains solutions to 5 homework assignments on trigonometric functions from a student named Victor Yahir Villamizar Villamizar. The assignments cover using the law of sines and cosines to solve triangles, calculating trigonometric ratios for right triangles, working with trigonometric identities, solving trigonometric equations, and applying trigonometry to solve a problem about forces. At the end, the student suggests using word searches and crosswords as didactic materials to help improve the learning system and communication with students and parents.
This document contains a student's work on several math exercises related to trigonometry. It includes solving problems using the law of sines and cosines. It also involves calculating trigonometric ratios for angles in right triangles, working through trigonometric identities, solving trigonometric equations, and applying trigonometry to solve a problem about forces. The student proposes using word searches with basic math formulas as a strategy to improve learning.
The document contains solutions to 4 problems posed at the IMC 2016 conference in Bulgaria.
The first problem proves that the sum of a sequence of positive numbers divided by increasing powers of 2 is less than or equal to 2. The second problem finds the minimum value of a function over continuous functions satisfying a given inequality.
The third problem proves that if a function satisfies three properties related to permutations, then the size of the ring it is defined over must be congruent to 2 modulo 4.
The fourth problem proves an inequality relating the number of integer solutions to an inequality when the upper bound is increased or decreased by 1.
The document discusses three NP-complete problems: subset sum, NAE-3-SAT, and max-cut. It provides proofs that subset sum and NAE-3-SAT are NP-complete by describing polynomial-time reductions from 3SAT. It also describes a polynomial-time reduction from NAE-3-SAT to show that max-cut is NP-complete.
The document defines and describes different types of sequences, including arithmetic, harmonic, and geometric sequences. It also discusses the convergence properties of sequences, defining convergent, divergent, and oscillating sequences. Some techniques for evaluating limits of convergent sequences are presented, including using continuous function representations and properties of polynomials.
The document discusses Pascal's triangle and the binomial theorem. It explains that the coefficients of the terms in the binomial expansion (a + b)^n are the elements of the nth row of Pascal's triangle. It also notes that in each term, the exponent of a decreases from n to 0 while the exponent of b increases from 0 to n.
This document discusses various matrix decomposition techniques including least squares, eigendecomposition, and singular value decomposition. It begins with an introduction to the importance of linear algebra and decompositions for applications. Then it provides examples of using least squares to fit curves to data and find regression lines. It defines eigenvalues and eigenvectors and provides examples of eigendecomposition. It also discusses diagonalization of matrices and using the eigendecomposition to raise matrices to powers. Finally, it discusses singular value decomposition and its applications.
The Euler-Mascheroni constant is calculated by three novel representations over these sets respectively: 1) Turán moments, 2) coefficients of Jensen polynomials for the Taylor series of the Riemann Xi function at s = 1/2 + i.t and 3) even coefficients of the Riemann Xi function around s = 1/2.
This document contains solutions to 5 homework assignments on trigonometric functions from a student named Victor Yahir Villamizar Villamizar. The assignments cover using the law of sines and cosines to solve triangles, calculating trigonometric ratios for right triangles, working with trigonometric identities, solving trigonometric equations, and applying trigonometry to solve a problem about forces. At the end, the student suggests using word searches and crosswords as didactic materials to help improve the learning system and communication with students and parents.
This document contains a student's work on several math exercises related to trigonometry. It includes solving problems using the law of sines and cosines. It also involves calculating trigonometric ratios for angles in right triangles, working through trigonometric identities, solving trigonometric equations, and applying trigonometry to solve a problem about forces. The student proposes using word searches with basic math formulas as a strategy to improve learning.
The document contains solutions to 4 problems posed at the IMC 2016 conference in Bulgaria.
The first problem proves that the sum of a sequence of positive numbers divided by increasing powers of 2 is less than or equal to 2. The second problem finds the minimum value of a function over continuous functions satisfying a given inequality.
The third problem proves that if a function satisfies three properties related to permutations, then the size of the ring it is defined over must be congruent to 2 modulo 4.
The fourth problem proves an inequality relating the number of integer solutions to an inequality when the upper bound is increased or decreased by 1.
The document discusses three NP-complete problems: subset sum, NAE-3-SAT, and max-cut. It provides proofs that subset sum and NAE-3-SAT are NP-complete by describing polynomial-time reductions from 3SAT. It also describes a polynomial-time reduction from NAE-3-SAT to show that max-cut is NP-complete.
The document defines and describes different types of sequences, including arithmetic, harmonic, and geometric sequences. It also discusses the convergence properties of sequences, defining convergent, divergent, and oscillating sequences. Some techniques for evaluating limits of convergent sequences are presented, including using continuous function representations and properties of polynomials.
The document discusses Pascal's triangle and the binomial theorem. It explains that the coefficients of the terms in the binomial expansion (a + b)^n are the elements of the nth row of Pascal's triangle. It also notes that in each term, the exponent of a decreases from n to 0 while the exponent of b increases from 0 to n.
This document discusses various matrix decomposition techniques including least squares, eigendecomposition, and singular value decomposition. It begins with an introduction to the importance of linear algebra and decompositions for applications. Then it provides examples of using least squares to fit curves to data and find regression lines. It defines eigenvalues and eigenvectors and provides examples of eigendecomposition. It also discusses diagonalization of matrices and using the eigendecomposition to raise matrices to powers. Finally, it discusses singular value decomposition and its applications.
The Euler-Mascheroni constant is calculated by three novel representations over these sets respectively: 1) Turán moments, 2) coefficients of Jensen polynomials for the Taylor series of the Riemann Xi function at s = 1/2 + i.t and 3) even coefficients of the Riemann Xi function around s = 1/2.
1. The document discusses vector calculus concepts including the dot product, cross product, gradient, divergence, and curl of vectors. It provides examples and explanations of how to calculate these quantities.
2. The dot product yields a scalar quantity and is used to calculate the angle between two vectors. The cross product yields a vector that is perpendicular to the plane of the two input vectors.
3. The gradient is the vector of partial derivatives of a scalar function and points in the direction of maximum increase. The divergence and curl are used to describe vector fields and involve taking partial derivatives.
The document discusses solving multiple non-linear equations using the multidimensional Newton-Raphson method. It provides an example of solving for the equilibrium conversion of two coupled chemical reactions. The key steps are: (1) writing the reaction equations in root-finding form as two non-linear equations f1 and f2; (2) defining the Jacobian matrix J with the partial derivatives of f1 and f2; and (3) using the multidimensional Taylor series expansion and Jacobian matrix to linearize the system and iteratively solve for the root where f1 and f2 equal zero.
Lecture-4 Reduction of Quadratic Form.pdfRupesh383474
The document discusses reducing a quadratic form to canonical form using an orthogonal transformation. It begins by defining quadratic forms and representing them using matrices. It then provides examples of writing the matrix and quadratic form for functions of 2 and 3 variables. The document explains finding the eigenvectors and eigenvalues of the coefficient matrix to form an orthogonal transformation matrix B. Premultiplying the coefficient matrix A by the inverse of B results in the diagonal canonical form matrix D, where the diagonal elements are the eigenvalues of A. The quadratic form is then in canonical (sum of squares) form. An example problem demonstrates reducing a 3D quadratic form to canonical form using this process.
I am Bella A. I am a Statistical Method In Economics Assignment Expert at economicshomeworkhelper.com/. I hold a Ph.D. in Economics. I have been helping students with their homework for the past 9 years. I solve assignments related to Economics Assignment.
Visit economicshomeworkhelper.com/ or email info@economicshomeworkhelper.com.
You can also call on +1 678 648 4277 for any assistance with Statistical Method In Economics Assignments.
For so many years now a lot of scientist have used the series of positive binomial expansion to solve that of Negative binomial expansion, positive fractional binomial expansion and Negative fractional binomial expansion which was generated/derived using Maclaurin series to derive the series of Negative binomial expansion, positive fractional binomial expansion and Negative fractional binomial expansion just as it was used to provide answers to positive binomial expansion but fails for All the other expansion due to a deviation made. This Manuscript contains the correct solution/answers to Negative binomial expansions with proofs through worked examples, with other forms of
solving Negative binomial expansion just as in the case of Pascal’s triangle in positive binomial expansion, in
Negative binomial expansion it is called Anekwe’s triangle and other methods like the combination method of solving Negative binomial expansion.
Lesson 4: Decimal to Scientific NotationKevin Johnson
This document contains a lesson on converting numbers between decimal and scientific notation. It includes examples of converting specific decimals to scientific notation by identifying the significant figures, moving the decimal point, and determining the power of 10. It also includes examples of performing calculations using numbers in scientific notation, such as multiplication and division, and ensuring the final answer is written with a coefficient between 1 and 9 and an appropriate power of 10. The document emphasizes the relationship between the power of 10 in scientific notation and the number of zeros in the number.
This document provides an introduction to matrices and their arithmetic operations. It defines what a matrix is, with m rows and n columns. It introduces basic matrix operations like addition, which is done element-wise, and multiplication by scalars. Matrix multiplication is defined as the sum of the products of corresponding entries of the first matrix's rows and second matrix's columns. Several examples are provided to illustrate these matrix operations.
6 2nd degree word problem, areas and volumes-xcTzenma
The document discusses 2nd degree equations and word problems that result in 2nd degree equations. It provides an example of finding two positive numbers given their product and the relationship between the numbers. The smaller number is defined as x, and the resulting equation 3x^2 - 2x - 96 = 0 is a 2nd degree equation. Another example involves calculating the maximum height reached by a stone thrown vertically upwards, which also results in solving a 2nd degree equation.
The document introduces concepts of vector algebra and geometry in two dimensions. It defines vectors, vector operations like addition and scalar multiplication, and properties including equality of vectors, parallelism, orthogonality, and the Cauchy-Schwarz inequality. It also covers vector representations geometrically as arrows, vector length, unit vectors, and linear combinations of vectors. Key concepts are illustrated with diagrams of vectors in the Cartesian plane.
This document provides an overview of algebraic techniques in combinatorics, including linear algebra concepts, partially ordered sets (posets), and examples of problems solved using these techniques. Some key points discussed are:
- Useful linear algebra facts such as rank, determinants, and vector/matrix properties
- Definitions and representations of posets, including Dilworth's theorem relating chains and antichains
- Examples of combinatorial problems solved using linear algebra tools such as vectors/matrices or applying Dilworth's theorem to obtain a divisibility relation poset
The binomial theorem provides a formula for expanding binomial expressions of the form (a + b)^n. It states that the terms of the expansion are determined by binomial coefficients. Pascal's triangle is a mathematical arrangement that shows the binomial coefficients and can be used to determine the coefficients in a binomial expansion. The proof of the binomial theorem uses mathematical induction to show that the formula holds true for any positive integer value of n.
On Application of Power Series Solution of Bessel Problems to the Problems of...BRNSS Publication Hub
One of the most powerful techniques available for studying functions defined by differential equations is to produce power series expansions of their solutions when such expansions exist. This is the technique I now investigated, in particular, its feasibility in the solution of an engineering problem known as the problem of strut of variable moment of inertia. In this work, I explored the basic theory of the Bessel’s function and its power series solution. Then, a model of the problem of strut of variable moment of inertia was developed into a differential equation of the Bessel’s form, and finally, the Bessel’s equation so formed was solved and result obtained.
This document discusses power series solutions to differential equations, specifically Bessel's equations. It provides background on power series expansions and their properties. It explains that solutions to differential equations can be written as power series when the coefficients of the equation are analytic at a point. As an example, it finds the general solution to a second order differential equation using the power series method. In summary, it outlines techniques for solving differential equations using power series expansions at ordinary points.
This document discusses applying power series solutions of Bessel equations to solve problems involving struts with variable moments of inertia. It begins by reviewing the basics of power series solutions to differential equations and Bessel equations. It then develops a model of the variable strut problem as a Bessel-form differential equation. Finally, it solves this equation using the power series method for Bessel equations to obtain a result for problems involving struts with non-constant moments of inertia.
This document provides instructions for a mathematics scholarship test consisting of 45 multiple-choice questions across 3 sections: Algebra, Analysis, and Geometry. The instructions specify that candidates should answer each question in the provided answer booklet rather than on the question paper. Various mathematical terms and notation are defined for reference. The questions cover a wide range of topics in higher mathematics including algebra, analysis, geometry, and complex analysis.
This document contains solutions to 5 problems posed at the IMC 2017 conference. The solutions are summarized as follows:
1) The possible eigenvalues of the matrix A described in Problem 1 are 0, 1, and -1±√3i/2.
2) Problem 2 proves that for any differentiable function f satisfying the Lipschitz condition, f(x)2 < 2Lf(x) for all x.
3) Problem 3 shows that for any set S subset of {1,2,...,2017}, there exists an integer n such that the sequence ak(n) defined in the problem satisfies the property that ak(n) is a perfect square if and only if k is
This document discusses using recurrence relations to model problems involving counting techniques. It provides examples of modeling problems related to bacteria population growth, rabbit population growth, the Tower of Hanoi puzzle, and valid codeword enumeration. For each problem, it defines the recurrence relation and initial conditions, derives a closed-form solution, and proves its correctness using mathematical induction. Recurrence relations provide a way to define sequences and solve problems recursively by relating terms to previous terms in the sequence.
The document discusses brute force algorithms. It provides examples of problems that can be solved using brute force, including sorting algorithms like selection sort and bubble sort. It then summarizes two geometric problems - the closest pair problem and the convex hull problem - and provides pseudocode for brute force algorithms to solve each problem. The time complexity of these brute force algorithms is O(n^3).
Cs6402 design and analysis of algorithms may june 2016 answer keyappasami
The document discusses algorithms and complexity analysis. It provides Euclid's algorithm for computing greatest common divisor, compares the orders of growth of n(n-1)/2 and n^2, and describes the general strategy of divide and conquer methods. It also defines problems like the closest pair problem, single source shortest path problem, and assignment problem. Finally, it discusses topics like state space trees, the extreme point theorem, and lower bounds.
1. The document discusses vector calculus concepts including the dot product, cross product, gradient, divergence, and curl of vectors. It provides examples and explanations of how to calculate these quantities.
2. The dot product yields a scalar quantity and is used to calculate the angle between two vectors. The cross product yields a vector that is perpendicular to the plane of the two input vectors.
3. The gradient is the vector of partial derivatives of a scalar function and points in the direction of maximum increase. The divergence and curl are used to describe vector fields and involve taking partial derivatives.
The document discusses solving multiple non-linear equations using the multidimensional Newton-Raphson method. It provides an example of solving for the equilibrium conversion of two coupled chemical reactions. The key steps are: (1) writing the reaction equations in root-finding form as two non-linear equations f1 and f2; (2) defining the Jacobian matrix J with the partial derivatives of f1 and f2; and (3) using the multidimensional Taylor series expansion and Jacobian matrix to linearize the system and iteratively solve for the root where f1 and f2 equal zero.
Lecture-4 Reduction of Quadratic Form.pdfRupesh383474
The document discusses reducing a quadratic form to canonical form using an orthogonal transformation. It begins by defining quadratic forms and representing them using matrices. It then provides examples of writing the matrix and quadratic form for functions of 2 and 3 variables. The document explains finding the eigenvectors and eigenvalues of the coefficient matrix to form an orthogonal transformation matrix B. Premultiplying the coefficient matrix A by the inverse of B results in the diagonal canonical form matrix D, where the diagonal elements are the eigenvalues of A. The quadratic form is then in canonical (sum of squares) form. An example problem demonstrates reducing a 3D quadratic form to canonical form using this process.
I am Bella A. I am a Statistical Method In Economics Assignment Expert at economicshomeworkhelper.com/. I hold a Ph.D. in Economics. I have been helping students with their homework for the past 9 years. I solve assignments related to Economics Assignment.
Visit economicshomeworkhelper.com/ or email info@economicshomeworkhelper.com.
You can also call on +1 678 648 4277 for any assistance with Statistical Method In Economics Assignments.
For so many years now a lot of scientist have used the series of positive binomial expansion to solve that of Negative binomial expansion, positive fractional binomial expansion and Negative fractional binomial expansion which was generated/derived using Maclaurin series to derive the series of Negative binomial expansion, positive fractional binomial expansion and Negative fractional binomial expansion just as it was used to provide answers to positive binomial expansion but fails for All the other expansion due to a deviation made. This Manuscript contains the correct solution/answers to Negative binomial expansions with proofs through worked examples, with other forms of
solving Negative binomial expansion just as in the case of Pascal’s triangle in positive binomial expansion, in
Negative binomial expansion it is called Anekwe’s triangle and other methods like the combination method of solving Negative binomial expansion.
Lesson 4: Decimal to Scientific NotationKevin Johnson
This document contains a lesson on converting numbers between decimal and scientific notation. It includes examples of converting specific decimals to scientific notation by identifying the significant figures, moving the decimal point, and determining the power of 10. It also includes examples of performing calculations using numbers in scientific notation, such as multiplication and division, and ensuring the final answer is written with a coefficient between 1 and 9 and an appropriate power of 10. The document emphasizes the relationship between the power of 10 in scientific notation and the number of zeros in the number.
This document provides an introduction to matrices and their arithmetic operations. It defines what a matrix is, with m rows and n columns. It introduces basic matrix operations like addition, which is done element-wise, and multiplication by scalars. Matrix multiplication is defined as the sum of the products of corresponding entries of the first matrix's rows and second matrix's columns. Several examples are provided to illustrate these matrix operations.
6 2nd degree word problem, areas and volumes-xcTzenma
The document discusses 2nd degree equations and word problems that result in 2nd degree equations. It provides an example of finding two positive numbers given their product and the relationship between the numbers. The smaller number is defined as x, and the resulting equation 3x^2 - 2x - 96 = 0 is a 2nd degree equation. Another example involves calculating the maximum height reached by a stone thrown vertically upwards, which also results in solving a 2nd degree equation.
The document introduces concepts of vector algebra and geometry in two dimensions. It defines vectors, vector operations like addition and scalar multiplication, and properties including equality of vectors, parallelism, orthogonality, and the Cauchy-Schwarz inequality. It also covers vector representations geometrically as arrows, vector length, unit vectors, and linear combinations of vectors. Key concepts are illustrated with diagrams of vectors in the Cartesian plane.
This document provides an overview of algebraic techniques in combinatorics, including linear algebra concepts, partially ordered sets (posets), and examples of problems solved using these techniques. Some key points discussed are:
- Useful linear algebra facts such as rank, determinants, and vector/matrix properties
- Definitions and representations of posets, including Dilworth's theorem relating chains and antichains
- Examples of combinatorial problems solved using linear algebra tools such as vectors/matrices or applying Dilworth's theorem to obtain a divisibility relation poset
The binomial theorem provides a formula for expanding binomial expressions of the form (a + b)^n. It states that the terms of the expansion are determined by binomial coefficients. Pascal's triangle is a mathematical arrangement that shows the binomial coefficients and can be used to determine the coefficients in a binomial expansion. The proof of the binomial theorem uses mathematical induction to show that the formula holds true for any positive integer value of n.
On Application of Power Series Solution of Bessel Problems to the Problems of...BRNSS Publication Hub
One of the most powerful techniques available for studying functions defined by differential equations is to produce power series expansions of their solutions when such expansions exist. This is the technique I now investigated, in particular, its feasibility in the solution of an engineering problem known as the problem of strut of variable moment of inertia. In this work, I explored the basic theory of the Bessel’s function and its power series solution. Then, a model of the problem of strut of variable moment of inertia was developed into a differential equation of the Bessel’s form, and finally, the Bessel’s equation so formed was solved and result obtained.
This document discusses power series solutions to differential equations, specifically Bessel's equations. It provides background on power series expansions and their properties. It explains that solutions to differential equations can be written as power series when the coefficients of the equation are analytic at a point. As an example, it finds the general solution to a second order differential equation using the power series method. In summary, it outlines techniques for solving differential equations using power series expansions at ordinary points.
This document discusses applying power series solutions of Bessel equations to solve problems involving struts with variable moments of inertia. It begins by reviewing the basics of power series solutions to differential equations and Bessel equations. It then develops a model of the variable strut problem as a Bessel-form differential equation. Finally, it solves this equation using the power series method for Bessel equations to obtain a result for problems involving struts with non-constant moments of inertia.
This document provides instructions for a mathematics scholarship test consisting of 45 multiple-choice questions across 3 sections: Algebra, Analysis, and Geometry. The instructions specify that candidates should answer each question in the provided answer booklet rather than on the question paper. Various mathematical terms and notation are defined for reference. The questions cover a wide range of topics in higher mathematics including algebra, analysis, geometry, and complex analysis.
This document contains solutions to 5 problems posed at the IMC 2017 conference. The solutions are summarized as follows:
1) The possible eigenvalues of the matrix A described in Problem 1 are 0, 1, and -1±√3i/2.
2) Problem 2 proves that for any differentiable function f satisfying the Lipschitz condition, f(x)2 < 2Lf(x) for all x.
3) Problem 3 shows that for any set S subset of {1,2,...,2017}, there exists an integer n such that the sequence ak(n) defined in the problem satisfies the property that ak(n) is a perfect square if and only if k is
This document discusses using recurrence relations to model problems involving counting techniques. It provides examples of modeling problems related to bacteria population growth, rabbit population growth, the Tower of Hanoi puzzle, and valid codeword enumeration. For each problem, it defines the recurrence relation and initial conditions, derives a closed-form solution, and proves its correctness using mathematical induction. Recurrence relations provide a way to define sequences and solve problems recursively by relating terms to previous terms in the sequence.
The document discusses brute force algorithms. It provides examples of problems that can be solved using brute force, including sorting algorithms like selection sort and bubble sort. It then summarizes two geometric problems - the closest pair problem and the convex hull problem - and provides pseudocode for brute force algorithms to solve each problem. The time complexity of these brute force algorithms is O(n^3).
Cs6402 design and analysis of algorithms may june 2016 answer keyappasami
The document discusses algorithms and complexity analysis. It provides Euclid's algorithm for computing greatest common divisor, compares the orders of growth of n(n-1)/2 and n^2, and describes the general strategy of divide and conquer methods. It also defines problems like the closest pair problem, single source shortest path problem, and assignment problem. Finally, it discusses topics like state space trees, the extreme point theorem, and lower bounds.
Similar to Infinite series Lecture 4 to 7.pdf (20)
Travis Hills' Endeavors in Minnesota: Fostering Environmental and Economic Pr...Travis Hills MN
Travis Hills of Minnesota developed a method to convert waste into high-value dry fertilizer, significantly enriching soil quality. By providing farmers with a valuable resource derived from waste, Travis Hills helps enhance farm profitability while promoting environmental stewardship. Travis Hills' sustainable practices lead to cost savings and increased revenue for farmers by improving resource efficiency and reducing waste.
ANAMOLOUS SECONDARY GROWTH IN DICOT ROOTS.pptxRASHMI M G
Abnormal or anomalous secondary growth in plants. It defines secondary growth as an increase in plant girth due to vascular cambium or cork cambium. Anomalous secondary growth does not follow the normal pattern of a single vascular cambium producing xylem internally and phloem externally.
Phenomics assisted breeding in crop improvementIshaGoswami9
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
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Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...AbdullaAlAsif1
The pygmy halfbeak Dermogenys colletei, is known for its viviparous nature, this presents an intriguing case of relatively low fecundity, raising questions about potential compensatory reproductive strategies employed by this species. Our study delves into the examination of fecundity and the Gonadosomatic Index (GSI) in the Pygmy Halfbeak, D. colletei (Meisner, 2001), an intriguing viviparous fish indigenous to Sarawak, Borneo. We hypothesize that the Pygmy halfbeak, D. colletei, may exhibit unique reproductive adaptations to offset its low fecundity, thus enhancing its survival and fitness. To address this, we conducted a comprehensive study utilizing 28 mature female specimens of D. colletei, carefully measuring fecundity and GSI to shed light on the reproductive adaptations of this species. Our findings reveal that D. colletei indeed exhibits low fecundity, with a mean of 16.76 ± 2.01, and a mean GSI of 12.83 ± 1.27, providing crucial insights into the reproductive mechanisms at play in this species. These results underscore the existence of unique reproductive strategies in D. colletei, enabling its adaptation and persistence in Borneo's diverse aquatic ecosystems, and call for further ecological research to elucidate these mechanisms. This study lends to a better understanding of viviparous fish in Borneo and contributes to the broader field of aquatic ecology, enhancing our knowledge of species adaptations to unique ecological challenges.
When I was asked to give a companion lecture in support of ‘The Philosophy of Science’ (https://shorturl.at/4pUXz) I decided not to walk through the detail of the many methodologies in order of use. Instead, I chose to employ a long standing, and ongoing, scientific development as an exemplar. And so, I chose the ever evolving story of Thermodynamics as a scientific investigation at its best.
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EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...Sérgio Sacani
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s
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This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
1. Infinite Series
Anushaya Mohapatra
Department of Mathematics
BITS PILANI K K Birla Goa Campus, Goa
November 2, 2022
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 1 / 27
2. Infinite Series:
An infinite series is the sum of an infinite sequence
{an} of numbers:
a1 + a2 + a3 + · · ·
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 2 / 27
3. Infinite Series:
An infinite series is the sum of an infinite sequence
{an} of numbers:
a1 + a2 + a3 + · · ·
In this section we want to understand the meaning of
such an infinite sum and to develop methods to
calculate it.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 2 / 27
4. Infinite Series:
An infinite series is the sum of an infinite sequence
{an} of numbers:
a1 + a2 + a3 + · · ·
In this section we want to understand the meaning of
such an infinite sum and to develop methods to
calculate it.
In order to give meaning for the infinite sum, we just
consider the sum of the first n terms
sn = a1 + a2 + · · · + an =
n
X
k=1
ak.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 2 / 27
5. Infinite Series
We define the infinite sum by
∞
X
k=1
ak = a1 + a2 + a3 + · · · = lim
n→∞
sn
whenever the later limit exists.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 3 / 27
6. Infinite Series
We define the infinite sum by
∞
X
k=1
ak = a1 + a2 + a3 + · · · = lim
n→∞
sn
whenever the later limit exists.
For example consider the series
P∞
k=1 1/2k−1
.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 3 / 27
7. Infinite Series
We define the infinite sum by
∞
X
k=1
ak = a1 + a2 + a3 + · · · = lim
n→∞
sn
whenever the later limit exists.
For example consider the series
P∞
k=1 1/2k−1
.
sn =
n
X
k=1
1/2k−1
= 2 −
1
2n−1
, therefore we can say that
∞
X
k=1
1/2k−1
= lim
n→∞
2 −
1
2n−1
= 2
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 3 / 27
8. Infinite Series Conti.
Given a sequence of numbers {an}, an expression of
the form
a1 + a2 + a3 + · · · + an + · · · .
is called an infinite series. The number an is called
nth term of the series.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 4 / 27
9. Infinite Series Conti.
Given a sequence of numbers {an}, an expression of
the form
a1 + a2 + a3 + · · · + an + · · · .
is called an infinite series. The number an is called
nth term of the series.
The sequence {sn} defined by
sn =
n
X
k=1
ak = a1 + a2 + · · · an
is called the sequence of partial sums of the series
and sn is called nth partial sum.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 4 / 27
10. Infinite Series Conti.
Convergence and divergence of series:
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 5 / 27
11. Infinite Series Conti.
Convergence and divergence of series:
If the sequence {sn} of partial sums converges to a
limit L, we say the series converges and its sum is L.
In this case we also write
∞
X
k=1
ak = a1 + a2 + a3 + · · · = L = lim
n→∞
sn.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 5 / 27
12. Infinite Series Conti.
Convergence and divergence of series:
If the sequence {sn} of partial sums converges to a
limit L, we say the series converges and its sum is L.
In this case we also write
∞
X
k=1
ak = a1 + a2 + a3 + · · · = L = lim
n→∞
sn.
If the sequence {sn} of partial sums does not
converge, we say the the series diverges.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 5 / 27
13. Infinite Series Conti.
Geometric Series: Geometric series are series of the
form (for a, r ∈ R)
a + ar + ar2
+ · · · + arn−1
+ · · · =
∞
X
n=1
arn−1
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 6 / 27
14. Infinite Series Conti.
Geometric Series: Geometric series are series of the
form (for a, r ∈ R)
a + ar + ar2
+ · · · + arn−1
+ · · · =
∞
X
n=1
arn−1
Theorem 0.1.
If |r| 1 then the above geometric series converges and
a + ar + ar2
+ · · · + arn−1
+ · · · =
∞
X
n=1
arn−1
=
a
1 − r
.
if |r| ≥ 1, the series diverges.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 6 / 27
15. Infinite Series Conti.
Theorem 0.2 (The n-th term test).
If the series
∞
X
n=1
an converges, then an → 0.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 7 / 27
16. Infinite Series Conti.
Theorem 0.2 (The n-th term test).
If the series
∞
X
n=1
an converges, then an → 0.
Examples:
(a).
∞
X
n=1
n
√
n2 + 10
. (b).
∞
X
n=1
cos nπ.
(c).
∞
X
n=2
1
4n
. (d).
∞
X
n=1
1
n(n + 1)
.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 7 / 27
17. Infinite Series Conti.
Part (a): Consider the n-th term an =
P∞
n=1
n
√
n2+10
which converges to 1
not equal to 0, hence by the n-th term test the series diverges.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 8 / 27
18. Infinite Series Conti.
Part (a): Consider the n-th term an =
P∞
n=1
n
√
n2+10
which converges to 1
not equal to 0, hence by the n-th term test the series diverges.
Part (b): Here an = cos nπ = (−1)n which is not a convergent sequence
by the above theorem the series is divergent.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 8 / 27
19. Infinite Series Conti.
Part (a): Consider the n-th term an =
P∞
n=1
n
√
n2+10
which converges to 1
not equal to 0, hence by the n-th term test the series diverges.
Part (b): Here an = cos nπ = (−1)n which is not a convergent sequence
by the above theorem the series is divergent.
Part (c): Given series is geometric series with common ration r = 1/4
whose modulus value is less then 1, hence the series converges.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 8 / 27
20. Infinite Series Conti.
Part (a): Consider the n-th term an =
P∞
n=1
n
√
n2+10
which converges to 1
not equal to 0, hence by the n-th term test the series diverges.
Part (b): Here an = cos nπ = (−1)n which is not a convergent sequence
by the above theorem the series is divergent.
Part (c): Given series is geometric series with common ration r = 1/4
whose modulus value is less then 1, hence the series converges.
Part (d): an =
1
n(n+1)
= 1
n − 1
n+1, sn = 1 − 1
n+1 converges to 1 hence
the series is convergent.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 8 / 27
21. Theorem 0.3 (Algebra of Series).
Let
∞
X
n=1
an = A and
∞
X
n=1
bn = B. Then
1
∞
X
n=1
(an ± bn) =
∞
X
n=1
an ±
∞
X
n=1
bn = A ± B
2
∞
X
n=1
kan = k
∞
X
n=1
an = kA.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 9 / 27
22. Theorem 0.3 (Algebra of Series).
Let
∞
X
n=1
an = A and
∞
X
n=1
bn = B. Then
1
∞
X
n=1
(an ± bn) =
∞
X
n=1
an ±
∞
X
n=1
bn = A ± B
2
∞
X
n=1
kan = k
∞
X
n=1
an = kA.
Example: (a).
∞
X
n=1
2n
+ 3n
4n
; (b).
∞
X
n=1
5n
− 3n
4n
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 9 / 27
product and quotient rule
is absent....
23. Part (a):
∞
X
n=1
2n
+ 3n
4n
=
X
n
(2/3)n
+ (3/4)n
=
X
n
(2/3)n
+
X
n
(3/4)n
. By geometric series test
P
n(2/3)n
and
P
n(3/4)n
are convergent so their sum is
convergent by previous theorem.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 10 / 27
24. Part (a):
∞
X
n=1
2n
+ 3n
4n
=
X
n
(2/3)n
+ (3/4)n
=
X
n
(2/3)n
+
X
n
(3/4)n
. By geometric series test
P
n(2/3)n
and
P
n(3/4)n
are convergent so their sum is
convergent by previous theorem.
Part (b): Since
∞
X
n=1
5n
4n
is divergent and
∞
X
n=1
3n
4n
is
convergent, the given series is divergent.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 10 / 27
25. Series of non-negative terms:
∞
X
n=1
an with an ≥ 0.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 11 / 27
26. Series of non-negative terms:
∞
X
n=1
an with an ≥ 0.
Theorem 0.4.
A series
∞
X
n=1
an of non-negative terms converges if and
only if the sequence {sn} of its partial sums are bounded
from above.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 11 / 27
27. Series of non-negative terms:
∞
X
n=1
an with an ≥ 0.
Theorem 0.4.
A series
∞
X
n=1
an of non-negative terms converges if and
only if the sequence {sn} of its partial sums are bounded
from above.
Example:
1 Is the series
∞
X
n=1
1
n!
convergent?
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 11 / 27
28. Series of non-negative terms:
∞
X
n=1
an with an ≥ 0.
Theorem 0.4.
A series
∞
X
n=1
an of non-negative terms converges if and
only if the sequence {sn} of its partial sums are bounded
from above.
Example:
1 Is the series
∞
X
n=1
1
n!
convergent?Ans: Convergent.
2 Is the series
P∞
n=1
1
n (harmonic series) convergent?
NO.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 11 / 27
29. What can you say about the convergence of the series
P∞
n=1
1
n2 ?
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 12 / 27
30. What can you say about the convergence of the series
P∞
n=1
1
n2 ? It is convergent which follows from the
following theorem.
Integral Test:
Theorem 0.5.
Let {an} be a sequence of positive terms. Suppose that
an = f (n), where f (x) is a positive, continuous,
decreasing function of x for all x ≥ N (N is a positive
integer). Then the series
∞
X
n=N
an and the integral
Z ∞
N
f (x)dx both converge or diverge.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 12 / 27
31. Examples:
(a). Find the values of p for which the following series
converges
∞
X
n=1
1
np
=
1
1p
+
1
2p
+
1
3p
+ · · · +
1
np
+ · · · .
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 13 / 27
32. Examples:
(a). Find the values of p for which the following series
converges
∞
X
n=1
1
np
=
1
1p
+
1
2p
+
1
3p
+ · · · +
1
np
+ · · · .
Ans: The above series is convergent if and only if p 1.
Just apply integral test with the function f (x) = 1/xp
.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 13 / 27
33. Examples:
(a). Find the values of p for which the following series
converges
∞
X
n=1
1
np
=
1
1p
+
1
2p
+
1
3p
+ · · · +
1
np
+ · · · .
Ans: The above series is convergent if and only if p 1.
Just apply integral test with the function f (x) = 1/xp
.
(b). Test the convergence of
∞
X
n=1
1
1 + n2
?
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 13 / 27
34. Examples:
(a). Find the values of p for which the following series
converges
∞
X
n=1
1
np
=
1
1p
+
1
2p
+
1
3p
+ · · · +
1
np
+ · · · .
Ans: The above series is convergent if and only if p 1.
Just apply integral test with the function f (x) = 1/xp
.
(b). Test the convergence of
∞
X
n=1
1
1 + n2
?
Ans: it is convergent. Just apply integral test with the
function f (x) = 1/(1 + x2
).
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 13 / 27
35. Theorem 0.6 (The Comparison Test).
Let
P
an,
P
cn and
P
dn be series with non-negative
terms. Suppose that for some integer N
dn ≤ an ≤ cn for all n N.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 14 / 27
36. Theorem 0.6 (The Comparison Test).
Let
P
an,
P
cn and
P
dn be series with non-negative
terms. Suppose that for some integer N
dn ≤ an ≤ cn for all n N.
1 If
P
cn converges, then
P
an also converges.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 14 / 27
37. Theorem 0.6 (The Comparison Test).
Let
P
an,
P
cn and
P
dn be series with non-negative
terms. Suppose that for some integer N
dn ≤ an ≤ cn for all n N.
1 If
P
cn converges, then
P
an also converges.
2 If
P
dn diverges, then
P
an also diverges.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 14 / 27
38. Theorem 0.6 (The Comparison Test).
Let
P
an,
P
cn and
P
dn be series with non-negative
terms. Suppose that for some integer N
dn ≤ an ≤ cn for all n N.
1 If
P
cn converges, then
P
an also converges.
2 If
P
dn diverges, then
P
an also diverges.
Examples:
(a) Test the convergence of
∞
X
n=1
5
5n − 1
(b) Test the convergence of
∞
X
n=1
1
n!
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 14 / 27
39. Theorem 0.7 (Limit Comparison Test).
Suppose that an 0 and bn 0 for all n ≥ N for some
N ∈ N.
1 If limn→∞
an
bn
= c 0, then
P
an and
P
bn both
converge or diverge.
2 If limn→∞
an
bn
= 0 and
P
bn converges then
P
an
converges.
3 If limn→∞
an
bn
= ∞ and
P
bn diverges then
P
an
diverges.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 15 / 27
40. Theorem 0.7 (Limit Comparison Test).
Suppose that an 0 and bn 0 for all n ≥ N for some
N ∈ N.
1 If limn→∞
an
bn
= c 0, then
P
an and
P
bn both
converge or diverge.
2 If limn→∞
an
bn
= 0 and
P
bn converges then
P
an
converges.
3 If limn→∞
an
bn
= ∞ and
P
bn diverges then
P
an
diverges.
Examples: Test the convergence of the following:
(a).
P∞
n=1
100
10n+1, (b).
P∞
n=1
1
2n+10.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 15 / 27
41. Theorem 0.8 (The Ratio Test).
Let
P
an be a series with positive terms and suppose that
lim
n→∞
an+1
an
= ρ.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 16 / 27
42. Theorem 0.8 (The Ratio Test).
Let
P
an be a series with positive terms and suppose that
lim
n→∞
an+1
an
= ρ.
Then;
1 the series converges if ρ 1,
2 the series diverges if ρ 1
3 the test is inconclusive if ρ = 1.
Test the convergence of the following:
(a).
P∞
n=1
xn
n! , (b).
P∞
n=1
(2n)!
n!n! , (c).
P∞
n=1
1
n2
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 16 / 27
43. Theorem 0.9 (The root test).
Let
P
an be a series with positive terms and suppose that
lim
n→∞
n
√
an = ρ.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 17 / 27
44. Theorem 0.9 (The root test).
Let
P
an be a series with positive terms and suppose that
lim
n→∞
n
√
an = ρ.
Then;
1 the series converges if ρ 1,
2 the series diverges if ρ 1
3 the test is inconclusive if ρ = 1.
Discuss the convergence of the following:
(a).
P∞
n=1
1−n
3n−n2 , (b).
P∞
n=1
3n
n10 , (c).
P∞
n=1
n
n+2
n2
.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 17 / 27
45. Alternating series
Alternating series:
A series in which the terms are alternatively positive
and negative is called alternating series.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 18 / 27
46. Alternating series
Alternating series:
A series in which the terms are alternatively positive
and negative is called alternating series.
Any series of the form:
∞
X
n=1
(−1)n
an or
∞
X
n=1
(−1)n+1
an where an ≥ 0
is an alternating series.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 18 / 27
47. Alternating series
Alternating series:
A series in which the terms are alternatively positive
and negative is called alternating series.
Any series of the form:
∞
X
n=1
(−1)n
an or
∞
X
n=1
(−1)n+1
an where an ≥ 0
is an alternating series.
Examples:
∞
X
n=1
(−1)n
n
,
∞
X
n=1
(−4/3)n
,
∞
X
n=1
(−1)n
√
n.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 18 / 27
48. Theorem 0.10 (The alternating series test (Leibniz
Test)).
The series:
∞
X
n=1
(−1)n+1
an = a1 − a2 + a3 − a4 + · · ·
converges, if all three of the following conditions are
satisfied:
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 19 / 27
49. Theorem 0.10 (The alternating series test (Leibniz
Test)).
The series:
∞
X
n=1
(−1)n+1
an = a1 − a2 + a3 − a4 + · · ·
converges, if all three of the following conditions are
satisfied:
1 The an’s are positive.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 19 / 27
50. Theorem 0.10 (The alternating series test (Leibniz
Test)).
The series:
∞
X
n=1
(−1)n+1
an = a1 − a2 + a3 − a4 + · · ·
converges, if all three of the following conditions are
satisfied:
1 The an’s are positive.
2 The positive an’s are (eventually) non-increasing:
an ≥ an+1 for all n ≥ N, for some integer N.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 19 / 27
51. Theorem 0.10 (The alternating series test (Leibniz
Test)).
The series:
∞
X
n=1
(−1)n+1
an = a1 − a2 + a3 − a4 + · · ·
converges, if all three of the following conditions are
satisfied:
1 The an’s are positive.
2 The positive an’s are (eventually) non-increasing:
an ≥ an+1 for all n ≥ N, for some integer N.
3 an → 0 as n → ∞.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 19 / 27
52. Examples:
1 If p 0, then the alternating p-series
∞
X
n=1
(−1)n+1
np
= 1 −
1
2p
+
1
3p
− · · ·
converges.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 20 / 27
53. Examples:
1 If p 0, then the alternating p-series
∞
X
n=1
(−1)n+1
np
= 1 −
1
2p
+
1
3p
− · · ·
converges.
2 What can you say about the converges of
∞
X
n=1
(−1)n
2 + n
8n
?
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 20 / 27
54. Absolute convergence:
A series
P
an is said to converge absolutely (be
absolutely convergent) if the corresponding series of
absolute values,
P
|an|, converges.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 21 / 27
55. Absolute convergence:
A series
P
an is said to converge absolutely (be
absolutely convergent) if the corresponding series of
absolute values,
P
|an|, converges.
Examples:
P∞
n=1
(−1)n
np is absolutely convergent for p 1 and for
other values of p, the series is not absolutely
convergent.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 21 / 27
56. Absolute convergence:
A series
P
an is said to converge absolutely (be
absolutely convergent) if the corresponding series of
absolute values,
P
|an|, converges.
Examples:
P∞
n=1
(−1)n
np is absolutely convergent for p 1 and for
other values of p, the series is not absolutely
convergent.
Theorem 0.11.
If the series
P
an is absolutely convergent then it is
convergent.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 21 / 27
57. Conditional convergence:
If the series
P
an is convergent but not absolutely
convergent then we say that the series
P
an is
conditionally convergent.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 22 / 27
58. Conditional convergence:
If the series
P
an is convergent but not absolutely
convergent then we say that the series
P
an is
conditionally convergent.
P∞
n=1
(−1)n
np is conditionally convergent for 0 p ≤ 1.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 22 / 27
59. Conditional convergence:
If the series
P
an is convergent but not absolutely
convergent then we say that the series
P
an is
conditionally convergent.
P∞
n=1
(−1)n
np is conditionally convergent for 0 p ≤ 1.
P∞
n=1
cos(n)
n5/2
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 22 / 27
60. Conditional convergence:
If the series
P
an is convergent but not absolutely
convergent then we say that the series
P
an is
conditionally convergent.
P∞
n=1
(−1)n
np is conditionally convergent for 0 p ≤ 1.
P∞
n=1
cos(n)
n5/2 is absolutely convergent and hence it is
convergent.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 22 / 27
61. Conditional convergence:
If the series
P
an is convergent but not absolutely
convergent then we say that the series
P
an is
conditionally convergent.
P∞
n=1
(−1)n
np is conditionally convergent for 0 p ≤ 1.
P∞
n=1
cos(n)
n5/2 is absolutely convergent and hence it is
convergent.
P∞
n=1
sin(2n−1)π/2
n3/4
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 22 / 27
62. Conditional convergence:
If the series
P
an is convergent but not absolutely
convergent then we say that the series
P
an is
conditionally convergent.
P∞
n=1
(−1)n
np is conditionally convergent for 0 p ≤ 1.
P∞
n=1
cos(n)
n5/2 is absolutely convergent and hence it is
convergent.
P∞
n=1
sin(2n−1)π/2
n3/4 is conditionally convergent.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 22 / 27
63. Examples
Discuss whether the following series absolutely
convergence or conditionally convergence.
(a).
P∞
n=1(−1)n 1−n
3n−n2 , (b).
P∞
n=1(−1)n ln(n)
n
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 23 / 27
conditionally convergent Absolutely convergent
64. Conclusion: Summary of Tests
1 The n-th Term Test: Unless an → 0, the series diverges.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 24 / 27
65. Conclusion: Summary of Tests
1 The n-th Term Test: Unless an → 0, the series diverges.
2 Geometric series:
P
arn
converges if |r| 1; otherwise it
diverges.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 24 / 27
66. Conclusion: Summary of Tests
1 The n-th Term Test: Unless an → 0, the series diverges.
2 Geometric series:
P
arn
converges if |r| 1; otherwise it
diverges.
3 p-series:
P 1
np
converges if p 1; otherwise it diverges.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 24 / 27
67. Conclusion: Summary of Tests
1 The n-th Term Test: Unless an → 0, the series diverges.
2 Geometric series:
P
arn
converges if |r| 1; otherwise it
diverges.
3 p-series:
P 1
np
converges if p 1; otherwise it diverges.
4 Series with nonnegative terms: Try the Integral Test, Ratio
Test or Root Test. Try comparing to a known series with the
Comparison Test.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 24 / 27
68. Conclusion: Summary of Tests
1 The n-th Term Test: Unless an → 0, the series diverges.
2 Geometric series:
P
arn
converges if |r| 1; otherwise it
diverges.
3 p-series:
P 1
np
converges if p 1; otherwise it diverges.
4 Series with nonnegative terms: Try the Integral Test, Ratio
Test or Root Test. Try comparing to a known series with the
Comparison Test.
5 Series with some negative terms: Does
P
|an| converge? If
yes, so does
P
an, since absolute convergence implies
convergence.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 24 / 27
69. Conclusion: Summary of Tests
1 The n-th Term Test: Unless an → 0, the series diverges.
2 Geometric series:
P
arn
converges if |r| 1; otherwise it
diverges.
3 p-series:
P 1
np
converges if p 1; otherwise it diverges.
4 Series with nonnegative terms: Try the Integral Test, Ratio
Test or Root Test. Try comparing to a known series with the
Comparison Test.
5 Series with some negative terms: Does
P
|an| converge? If
yes, so does
P
an, since absolute convergence implies
convergence.
6 Alternating series: ±
P
(−1)n
an; (an ≥ 0) converges if the
series satisfies the conditions of the Alternating Series Test.
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 24 / 27
70. Examples
Determine whether the following series convergent or divergent.
1
P∞
n=1(3)n+1
(4)−n+1
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 25 / 27
71. Examples
Determine whether the following series convergent or divergent.
1
P∞
n=1(3)n+1
(4)−n+1
Ans:Convergent
2
∞
X
n=1
1 + cos n
en
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 25 / 27
72. Examples
Determine whether the following series convergent or divergent.
1
P∞
n=1(3)n+1
(4)−n+1
Ans:Convergent
2
∞
X
n=1
1 + cos n
en
Ans: Convergent
3
∞
X
n=1
(−1)n
√
n
3n + 5
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 25 / 27
73. Examples
Determine whether the following series convergent or divergent.
1
P∞
n=1(3)n+1
(4)−n+1
Ans:Convergent
2
∞
X
n=1
1 + cos n
en
Ans: Convergent
3
∞
X
n=1
(−1)n
√
n
3n + 5
Ans: Conditionally Convergent
4
∞
X
n=2
ln n
n
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 25 / 27
74. Examples
Determine whether the following series convergent or divergent.
1
P∞
n=1(3)n+1
(4)−n+1
Ans:Convergent
2
∞
X
n=1
1 + cos n
en
Ans: Convergent
3
∞
X
n=1
(−1)n
√
n
3n + 5
Ans: Conditionally Convergent
4
∞
X
n=2
ln n
n
Ans: Divergent
5
∞
X
n=1
n sin
1
n
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 25 / 27
75. Examples
Determine whether the following series convergent or divergent.
1
P∞
n=1(3)n+1
(4)−n+1
Ans:Convergent
2
∞
X
n=1
1 + cos n
en
Ans: Convergent
3
∞
X
n=1
(−1)n
√
n
3n + 5
Ans: Conditionally Convergent
4
∞
X
n=2
ln n
n
Ans: Divergent
5
∞
X
n=1
n sin
1
n
Ans: Divergent
Anushaya Mohapatra (Dept. of Maths) Infinite Series November 2, 2022 25 / 27