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ST2200/MS2020 - Excel Assignment 2025: ColaFizz

MS2020StatisticsBusiness analysis

A soft drinks company, named “ColaFizz”, has recently changed the type of bottle used for their drink. They previously used plastic bottles, and are now using cardboard bottles, which are friendlier for the environment.

EE4204/TEE4204 Computer Networks (Part 1) - Socket Programming Assignment (Sem1, 2024-25)

EE4204TEE4204Computer NetworksSocket ProgrammingTCP

Develop a TCP-based client-server socket program for transferring a large message. Here, the message transmitted from the client to server is read from a large file. The message is split into short data-units which are sent by using stop- and-wait flow control. Also, a data-unit sent could be damaged with some error probability.

MXB261 Modelling and Simulation Science - Assignment 2 - A Simulation Project - Modelling an Epidemic

MXB261Modelling and Simulation ScienceModelling an EpidemicLatin Hypercube SamplingMarkov ProcessMonte Carlo

The theme of this project is the effect of parameter values on the behaviour of a viral epidemic a mathematical model, in both a temporal and spatial setting.

CS6601 Artificial Intelligence - Assignment 3: Bayes Nets

Artificial IntelligenceBayes NetsPythonProbabilistic ReasoningQuantifying UncertaintyMarkov Chain

In this assignment, you will work with probabilistic models known as Bayesian networks to efficiently calculate the answer to probability questions concerning discrete random variables.

Major Assignment 2: Probability & Hypothesis Testing Case Study

Probability & Hypothesis Testing Case StudyStatisticsHypothesis TestingProbability ModelingInferential Statistical Modeling

You are the manager of a well-established supermarket chain with multiple business operations, including a popular retail store and a factory that produces essential goods. As part of your role, you regularly analyse business data to make informed decisions and optimise performance, leveraging statistical tools and insights.

Random Number Generation: ICDF Method for Inhomogeneous Exponential Distribution

Random Number GenerationICDFInhomogeneous Exponential Distribution

The Inverse Cumulative Distribution Function (ICDF) method is a general technique for generating random numbers from any probability distribution for which the CDF (Cumulative Distribution Function) has a well-defined inverse. Here's how to apply the ICDF method to generate random numbers from an inhomogeneous exponential distribution:

Mathematics for Computer Science Project 2: PAs-Modeling and CSI-Prediction

Behavioral modelingCSI-PredictionNMSEPython

The project requires completing one of the following two tasks, and when submitting, include the project code and a report. Various methods such as non-linear regression or deep learning can be employed.

MTH208 NUMERICAL ANALYSIS - Coursework II: Approximating the absolute value function

MTH208NUMERICAL ANALYSISApproximating the absolute value function

The objective of this project is to explore and compare various numerical methods (interpolation with various basis or fitting in discrete and continuous cases) for approximating the absolute value function. You may provide basic ideas of each numerical method, give the implementation details and then compare their performance in terms of accuracy, implementation details and computational efficiency (You don’t need to include the code in the report).

STAT5002 Introduction to Statistics Assignment: Housing Price Analysis

STAT5002Introduction to StatisticsHousing Price AnalysisR

Using the data provided, choose one country and create an informative chart describing housing prices. You may choose the time period to draw data from as well as the country. You may explain the chart in no more than five sentences. What does it mean? What story does it tell about your chosen country and residential price?

MATH4063 Case Studies in Mathematical Modeling - Group Project: Jet Lag

MATH4063Case Studies in Mathematical ModelingJet LagThe Best HospitalBoarding and Disembarking a Plane

Organizing international meetings is not easy in many ways, including the problem that some of the participants may experience the effects of jet lag after recent travel from their home country to the meeting location which may be in a different time-zone, or in a different climate and time of year, and so on. All these things may dramatically affect the productivity of the meeting.

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