Quick Correlation Coefficients vs DijkstraGraph

The correlation coefficient (commonly noted by the Greek letter rho, ρ) measures the degree to which two sets of numbers are related. The correlation coefficient can range from -1.000 to +1.000 with a 0 indicating that there is no relation between the two sets. A 'slider' data entry option allows rapid creation of numerical data. Additionally, you may use the 'keypad' data entry option to expand the numerical range beyond plus or minus 1,000. In this application, you may relate two or three sets of numbers and the correlations between the sets are shown as ρ(AB), ρ(AC), and ρ(BC), where the letters A, B, and C represent the columns. There must be at least 3 pairs of numbers in any 2 rows for the correlation coefficient to be computed. Zero is a number but 'n/a' is not. If, for example, Column A has 5 rows of numbers and the 6th row is 'n/a' and Column B has 4 rows of numbers and the 5th row is 'n/a', the correlation coefficient, ρ(AB), will be computed for the first 4 pairs of numbers.

Learn, Play, and Explore graph theory and Dijkstra's shortest path algorithm with DijkstraGraph! Create and edit simple graphs and add edge weights. Rearrange the vertices and interact with the adjacency matrix to explore graph and matrix structure. Play through Dijkstra's shortest path algorithm step by step to identify a shortest path between two vertices. Play through the algorithm on the connected graph you create or explore one already created for you! Create and edit simple graphs - Add and delete vertices and edges - Add and edit weights on each edge - Rearrange vertices to explore graph Interact with the adjacency matrix - Tap on a vertex or edge to highlight corresponding rows and columns in adjacency matrix Play or Explore Dijkstra's shortest path algorithm - Play through Dijkstra's shortest path algorithm on the graph you create! - Or Explore the algorithm on a built in demo graph - Choose a start and end vertex then follow the instructions to step through the algorithm - Complete each step successfully to advance to the next part of the algorithm - After completing the algorithm, use the results to identify the shortest path Run - Don't have time to play through the algorithm?  - Choose a start and end vertex and run the algorithm to identify shortest path