MATLAB Topics for Presentation

MATLAB for Data Analysis: Techniques for importing, analyzing, and visualizing data.
Data Analysis with MATLAB.
Getting Started with MATLAB.
Calculus with MATLAB
MATLAB for Linear Algebra
MATLAB for Scientific Computing
Applications of MATLAB in Mathematics Research
Introduction to MATLAB: Basic commands, syntax, and environment.
MATLAB for Statistics: Descriptive statistics, hypothesis testing, regression analysis, and data visualization.
Linear Regression: Implement a simple linear regression algorithm to fit a line to a set of data points and visualize the regression line.
Data Visualization: Explore MATLAB’s plotting capabilities by creating various types of plots (line plots, scatter plots, histograms) using sample datasets.
Visualizing Functions: Plot various mathematical functions (e.g., trigonometric, exponential, logarithmic) and explore how they change with different parameters. Animate the functions to see their behavior dynamically.
Analyzing Stock Data: Download real or simulated stock market data and calculate basic statistics (mean, standard deviation) or plot price trends over time.
Creating Infographics: Use MATLAB to generate visually appealing infographics representing mathematical data or concepts.
Script Files and M-Functions
Basic Functions
Arrays and Matrices
Plotting and Visualization
Data Import and Manipulation: Show how to import data into MATLAB from different file formats (e.g., Excel, CSV) and perform basic data manipulation tasks like filtering, sorting, and extracting subsets of data.
MATLAB Interface Tour: Walk through the MATLAB interface, highlighting key elements such as the Command Window, Workspace, Current Folder, and Editor.
MATLAB Live Scripts: Introduce Live Scripts, which combine code, output, and formatted text in a single interactive document. Show how to create and use Live Scripts for analysis and documentation.
MATLAB Resources and Support: Direct beginners to MATLAB documentation, online tutorials, and community forums for additional learning resources and support.
Efficiency Tips: Share tips and tricks for efficient MATLAB usage, including keyboard shortcuts, debugging techniques, and coding best practices.
Symbolic Mathematics with MATLAB: Introduce MATLAB’s Symbolic Math Toolbox and demonstrate how it can be used for symbolic computations, including symbolic differentiation, integration, solving algebraic equations, and simplifying expressions.
Probability and Statistics with MATLAB: Show how MATLAB can be used for statistical analysis, including probability distributions, hypothesis testing, regression analysis, and Monte Carlo simulations.
Numerical Methods and MATLAB: Explore how MATLAB can be used to implement and visualize various numerical methods such as numerical integration, solving differential equations, root finding, and optimization techniques.
MATLAB Programming Constructs: Covering loops, conditional statements, and other programming constructs in MATLAB.
MATLAB Graphics: Exploring MATLAB’s graphical capabilities, including creating plots, histograms, and scatter plots.
MATLAB Live Editor: Introducing the Live Editor feature in MATLAB and how it allows for interactive coding and documentation.
MATLAB Resources and Help: Providing guidance on accessing MATLAB documentation, online resources, and community support for beginners.
MATLAB Programming Best Practices: Tips and tricks for writing efficient, readable, and maintainable MATLAB code.
MATLAB for Mathematics: Highlighting MATLAB’s capabilities for mathematical computations, symbolic mathematics, and numerical methods.
MATLAB Integration with Other Tools: Demonstrating how MATLAB can be integrated with other software tools and languages like Python, Excel, and LaTeX.
emperature Converter: Develop a MATLAB program that converts temperature between Celsius, Fahrenheit, and Kelvin scales based on user input.
BMI Calculator: Build a MATLAB script that calculates Body Mass Index (BMI) based on user input of weight (in kilograms) and height (in meters), and provides a classification of underweight, normal weight, overweight, or obese.
Data Visualization: Use MATLAB to visualize data from a CSV file, such as temperature or stock market data, by plotting time-series graphs and analyzing trends.
Control Flow Statements in MATLAB
Function Visualizer: Create a program that prompts the user to enter a mathematical function (e.g., sin(x), x^2 + 2x) and plots the function over a specified range. This reinforces understanding of function behavior and visualization techniques.
Prime Number Checker: Write a program that takes a number as input and determines whether it’s prime. Utilize for loops and conditional statements to check for divisibility by smaller numbers. This project practices loop logic and basic number theory.
Interactive Calculus: Develop a program that allows users to input a function and choose between finding its derivative or integral. The program should then calculate and display the result. This exercise combines mathematical concepts with MATLAB’s symbolic computation capabilities.
Coin Flip Simulator: Simulate coin flips (or dice rolls) for a specified number of trials. Calculate and display the probability of heads (or specific dice outcomes) and visualize the results using a bar chart. This project introduces concepts like random number generation and data visualization.
Stock Market Analysis (Basic): Download a sample dataset of historical stock prices (available online) and calculate basic statistics like mean, standard deviation, or minimum/maximum values. Optionally, plot the price trend over time to explore basic data analysis techniques.
Budget Tracker: Design a program that allows users to input their income and expenses for different categories. Calculate the total expenditure and remaining balance. This project practices user input, calculations, and potentially formatting output for readability.