-1 2 2 0 x = -1 -4 1 -6 Answer: a = 0 and b = -6
Here is an example code snippet in MATLAB that converts a string into a matrix: str = '123456789'; % input string numChars = length(str); % number of characters in the string matrixSize = ceil(sqrt(numChars)); % calculate the size of the resulting matrix % pad the string with zeros to make it divisible by the matrix size str = [str, num2str(zeros(1, matrixSize^2 - numChars))]; % reshape the string into a matrix matrix = reshape(str, matrixSize, matrixSize); This code takes an input string and calculates the size of the matrix needed to store all the characters. It then pads the string with zeros to make it divisible by the matrix size. Finally, it uses the reshape function to convert the string into a matrix.
Correlation and regression analysis can help business to investigate the determinants of key variables such as their sales. Variations in a companies sales are likely to be related to variation in product prices,consumers,incomes,tastes and preference's multiple regression analysis can be used to investigate the nature of this relationship and correlation analysis can be used to test the goodness of fit. Regression can also be used to estimate the trend in a time series to make forecast
To help in the differential diagnosis of different types of anemia; To assess the severity of anemia and monitor the treatment of patients with chronic anemia; To evaluate protein depletion
#include<stdio.h> #include<math.h> float detrm(float[][],float); void cofact(float[][],float); void trans(float[][],float[][],float); main() { float a[25][25],k,d; int i,j; printf("ENTER THE ORDER OF THE MATRIX:\n"); scanf("%f",&k); printf("ENTER THE ELEMENTS OF THE MATRIX:\n"); for(i=0;i<k;i++) { for(j=0;j<k;j++) { scanf("%f",&a[i][j]); } } d=detrm(a,k); printf("THE DETERMINANT IS=%f",d); if(d==0) printf("\nMATRIX IS NOT INVERSIBLE\n"); else cofact(a,k); } /******************FUNCTION TO FIND THE DETERMINANT OF THE MATRIX************************/ float detrm(float a[25][25],float k) { float s=1,det=0,b[25][25]; int i,j,m,n,c; if(k==1) { return(a[0][0]); } else { det=0; for(c=0;c<k;c++) { m=0; n=0; for(i=0;i<k;i++) { for(j=0;j<k;j++) { b[i][j]=0; if(i!=0&&j!=c) { b[m][n]=a[i][j]; if(n<(k-2)) n++; else { n=0; m++; } } } } det=det+s*(a[0][c]*detrm(b,k-1)); s=-1*s; } } return(det); } /*******************FUNCTION TO FIND COFACTOR*********************************/ void cofact(float num[25][25],float f) { float b[25][25],fac[25][25]; int p,q,m,n,i,j; for(q=0;q<f;q++) { for(p=0;p<f;p++) { m=0; n=0; for(i=0;i<f;i++) { for(j=0;j<f;j++) { b[i][j]=0; if(i!=q&&j!=p) { b[m][n]=num[i][j]; if(n<(f-2)) n++; else { n=0; m++; } } } } fac[q][p]=pow(-1,q+p)*detrm(b,f-1); } } trans(num,fac,f); } /*************FUNCTION TO FIND TRANSPOSE AND INVERSE OF A MATRIX**************************/ void trans(float num[25][25],float fac[25][25],float r) { int i,j; float b[25][25],inv[25][25],d; for(i=0;i<r;i++) { for(j=0;j<r;j++) { b[i][j]=fac[j][i]; } } d=detrm(num,r); inv[i][j]=0; for(i=0;i<r;i++) { for(j=0;j<r;j++) { inv[i][j]=b[i][j]/d; } } printf("\nTHE INVERSE OF THE MATRIX:\n"); for(i=0;i<r;i++) { for(j=0;j<r;j++) { printf("\t%f",inv[i][j]); } printf("\n"); } } ALTERNATIVE CODE: #include<iostream.h> #include<stdio.h> #include<conio.h> #include<process.h> #include<math.h> // Written by Ran // There have been enough comments to help the reader easily understand this program // Helpfulness of COMMENTS in this program and Pre-requisites:- // a. However it's assumed that the reader is familiar with the basics of C++ // b. It is also assumed that the reader knows the basic mathematics involving matrices. // c. Since this program focusses on how to find inverse of a matrix, the comments // in the program are sufficient for understanding this. // It is assumed that the reader is familiar with basics of matrices in C++ (like input, display, // addition,transpose,etc. of matrices) // The comments in this program aim to explain the reader how to find inverse // d. Hence through comments, the reader will also be taught how to find determinant, // adjoint, cofactor,etc. However as said in the previous lines, there won't be comments // for explaining basics like input,display,etc of a matrix using C++. // NOTES: // 1. float datatype has been used for matrix, determinant. // 2. To have consistency between mathematics and C++, this program considers a[1][1] as the first element // i.e row and column indices begin with 1 same as mathematics. // Define a structure matrix with a matrix (2D array of type float) and size n // Declare the objects of this structure used in this program struct matrix { float a[25][25]; int n; }obj,c_obj,trans_obj,obj_cof,obj_adj,obj_inv; // Prototypes of the functions used in this program void input(matrix&); void display(matrix&); matrix reduced(matrix &, int ,int ); float determinant(matrix); float cofactor(matrix,int,int); matrix transpose(matrix); matrix adjoint(matrix); matrix inverse(matrix obj); // Begining of Main function int main() { // Getting dimensions input by the user int r,c; again: cout<<"Enter the order of the matrix: "<<endl; cout<<"Enter Row dimension: "; cin>>r; cout<<"Enter Column dimension: "; cin>>c; // Check dimensions for square matrix so that inverse can be found // If user enters different dimensions for row and column, ask to re-enter or quit program if(r!=c) { char ans; cout<<"Inverse can be found out only for a square matrix. Enter same dimension for row and column. Do you want to enter the dimensions again? Press Y for yes"<<endl; cin>>ans; if(ans=='y') goto again; else cout<<"Program exit"; getch(); exit(0); } // If it's a square matrix, proceed else if(r==c) {obj.n=r;} cout<<endl; input(obj); // call input function to input the matrix elements from the user display(obj); // display the matrix got as input now // Following lines were used to test parts/sections/segments of the code and hence commented /* char ans2; cout<<"do u want to check reduce matrix? Press y to check reduce matrix and press any char to skip this"<<endl; cin>>ans2; if(ans2=='y') { int i,j; cout<<"Enter row i and col j to get reduced matrix"<<endl; cin>>i>>j; // i=i-1; // j=j-1; c_obj=reduced(obj,i,j); char ans1; cout<<"Do you want to display the reduced matrix? If yes, Press y "<<endl; cin>>ans1; if(ans1=='y') { cout<<"Displaying reduced matrix..."<<endl; display(c_obj); } }*/ //Find Determinant cout<<"Finding determinant......"<<endl; cout<<"The determinant is"<<determinant(obj)<<endl; //Find Cofactor if user wishes to char ans3; cout<<"Do you want to find cofactor? Press y if yes"<<endl; cin>>ans3; while(ans3=='y') { int i,j; cout<<"Finding cofactor. Enter row and column"<<endl; cin>>i>>j; cout<<"Cofactor of a["<<i<<"]["<<j<<"] is "<<cofactor(obj,i,j)<<endl; cout<<"want of find cofactor of another element? Press y for yes"<<endl; cin>>ans3; } // Following lines were to meant to test ONLY the transpose function and hence commented /* cout<<"Printing Transpose of the matrix "<<endl; matrix trans1; trans1=transpose(obj); display(trans1); */ // Find Inverse cout<<"\n\n\n Finding Inverse. . .\n\n"; matrix obj_inv2; obj_inv2=inverse(obj); display(obj_inv2); // Display the matrix inverse getch(); return 0; } void input(matrix &obj) { // This function gets elements of a matrix input by the user // Parameter is the structure object obj (used throughout the program) // Parameter is "passed by reference" so as to reflect the changes made by this function, to other functions that call it cout<<"Enter the matrix "<<endl; for (int i=1;i<=obj.n;i++) { for (int j=1;j<=obj.n;j++) { cout<<"Enter the element a["<<i<<"]["<<j<<"] : "; cout<<endl; cin>>obj.a[i][j]; } } } void display(matrix &obj) { // This function displays elements of a matrix passed to it as a parameter // Parameter is the structure object obj (used throughout the program) // Parameter is "passed by reference" but may be "passed by value" also. if(obj.n==0) return; else{ cout<<"The matrix is: "<<endl; for (int i=1;i<=obj.n;i++) { for (int j=1;j<=obj.n;j++) { cout<<obj.a[i][j]<<" "; } cout<<endl; } }} matrix reduced(matrix &obj, int i,int j) { // This function reduces the matrix passed as input to it // The 'reduction' requirement is like this: // Eliminate the row i and column j from the given matrix to get the reduced matrix // This is done by the following logic: // a is given matrix. c_obj is desired reduced matrix // i. Using two for loops (iterating with p and q here) as usual, we scan the given matrix. // row and col represent the current location pointer of row and column of the required reduced matrix. // ii. All elements from given matrix are copied to reduced matrix except for those corresponding to // row i and column j // iii. The reduced matrix has its dimensions one less than that of given matrix int row=1,col=1; for(int p=1;p<=obj.n;p++) // outer loop traverses through rows as usual { for(int q=1;q<=obj.n;q++) // inner loop traverses through columns as usual { if((p!=i)&&(q!=j)) // Skip the elements corresponding to row i OR column j of the given matrix { c_obj.a[row][col]=obj.a[p][q]; col=col+1; } if(col>=obj.n) // When column 'col' of reduced matrix reaches (or exceeds n), reset it to 1 { // and increment 'row'. This means current row of reduced matrix got filled and // we need to begin filling a new row. col=1; row=row+1; if (row>=obj.n) //This represents the case when both 'col' and 'row of reduce matrix reach (or // exceed) n. This means the reduced matrix has been filled up.Break out of the loops. break; } } } c_obj.n=obj.n-1; // Fix the dimension of the reduced matrix one less than the given input matrix return c_obj; // Return the reduced matrix to the calling function. } float determinant(matrix obj) { // This function is called recursively until we get dimension = 1 where the only element in the matrix gets returned. float det=0; if(obj.n==1) {return obj.a[1][1]; } else { for(int scan=1;scan<=obj.n;scan++)//Fix the first row and vary the column in this row using for loop iteration variable 'scan' { det=det+obj.a[1][scan]*int(pow(-1,(1+scan)))*determinant(reduced(obj,1,scan)); // det is calculated to be the sum of the following // i. prev value stored in det. // ii. current element in the first row (i.e. a[1][scan]) MULTIPLIED by -1^(i+j) [i is 1 for 1st row and j is nothing but scan here MULTIPLIED by the reduced matrix corresponding to this i (1) and j (scan) // PLEASE UNDERSTAND BY COMPARING THIS WITH THE MATHEMATICAL WAY OF CALCULATING DETERMINANT // - It's computed in a similar way here. } return det; } } float cofactor(matrix obj,int i,int j) { // The computation done here is like this: // If the matrix (passed as paramenter) has dimension = 1, return the only element as cofactor // Else, return determinant of the reduced matrix corresponding to i and j passed with a // multiplication factor -1^(i+j) float cofact; if(obj.n==1) { return obj.a[1][1]; } else { cofact=int(pow(-1,(i+j)))*determinant(reduced(obj,i,j)); } return cofact; } matrix transpose(matrix obj) { // Transpose matrix is the given matrix with its rows and columns interchanged. // Just invert the elements during storing when scanning through the for loops // trans_obj is the transposed matrix, returned by the function. // obj is the input matrix passed to this function. trans_obj.n=obj.n; for(int i=1;i<=obj.n;i++) { for(int j=1;j<=obj.n;j++) { trans_obj.a[i][j]=obj.a[j][i]; } } return trans_obj; } matrix adjoint(matrix obj) { // obj_adj is adjoint matrix and obj_cof is cofactor matrix // both have dimensions n // Cofactor matrix of a given matrix is a matrix whose elements are the cofactors of the respective // elements of the given matrix // Adjoint matrix is transpose of cofactor matrix. Return this obj_adj.n=obj.n; obj_cof.n=obj.n; for(int i=1;i<=obj.n;i++) { for(int j=1;j<=obj.n;j++) { obj_cof.a[i][j]=cofactor(obj,i,j); } } obj_adj=transpose(obj_cof); return obj_adj; } matrix inverse(matrix obj) { // Formula : Inverse of a matrix is = adj(matrix)/its determinant float d=determinant(obj); // First find determinant of the given matrix matrix obj_null; obj_null.n=0; // Display error message if determinant is 0 if(d==0) { cout<<"Inverse can be found only if the determninant of the matrix is non-zero"<<endl; return obj_null; } // Determinant is non-zero - Proceed finding inverse using the above formula else { matrix obj_adj1=adjoint(obj); obj_adj1.n=obj.n; obj_inv.n=obj.n; for(int i=1;i<=obj.n;i++) { for(int j=1;j<=obj.n;j++) { obj_inv.a[i][j]=(obj_adj1.a[i][j])/d; } } return obj_inv; } }
correlation measure the strength of association between to variables.but some times both variables are not in same units.so we cannot measure it with the help of correlation. in this case we use its coefficent which mean unit free. that,s why we use it.
The possible range of correlation coefficients depends on the type of correlation being measured. Here are the types for the most common correlation coefficients: Pearson Correlation Coefficient (r) Spearman's Rank Correlation Coefficient (ρ) Kendall's Rank Correlation Coefficient (τ) All of these correlation coefficients ranges from -1 to +1. In all the three cases, -1 represents negative correlation, 0 represents no correlation, and +1 represents positive correlation. It's important to note that correlation coefficients only measure the strength and direction of a linear relationship between variables. They do not capture non-linear relationships or establish causation. For better understanding of correlation analysis, you can get professional help from online platforms like SPSS-Tutor, Silverlake Consult, etc.
how much did the study cost
To assess the effect significant moments had on the author's life.
To assess means to observe, see, evaluate a situation before you make any decision or action. You can also re-assess after you act on a decision or perform an action to determine the effectiveness of your action. To assist means to help.
Other methods that can be used for decision-making include cost-benefit analysis, SWOT analysis, decision matrix, and scenario planning. These methods can help assess the advantages, disadvantages, risks, and potential outcomes of a decision beyond what is captured in a feasibility report.
The benefit of using correlation and regression analysis in business decisions is that it allows you to weigh outcomes. This can help managers see if they should continue with their current model or make changes to it.
yes
There are a few methods that can help to assess the status of the biosphere. They include soil samples, air samples, and capturing photographs of ecosystems.
Yes, the primary organic fibers found in cartilage matrix are collagen fibers. These fibers provide strength and structure to the cartilage tissue. Additionally, there are proteoglycans and glycoproteins present in the matrix that help maintain its integrity and function.
Yes, occupational therapy can help you to choose a new career. They will assess your strengths and interest to help you select a suitable career.
Many places on the internet offer this service, even for free. Tools such as SWOT analysis, PEST analysis , Ansoff Matrix, and Boston Matrix can help you along the way as you write and outline our buisness and marketing stratergy.