Lecture

Data Analysis Techniques: Amplitude Shift Keying and Graphical Methods

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In course

MICRO-110: Probability & statistics for engineers

This course covers the basics of probability and statistical techniques for engineers, including major probability concepts, data analysis, and statistical inference.

Description

This lecture introduces amplitude shift keying (ASK) as a method for encoding data in communication systems. The instructor explains the basic principles of ASK, including how the amplitude of a carrier signal varies to represent binary data. The lecture emphasizes the importance of statistical analysis and graphical representation of data, using Jupyter Notebooks for practical exercises. Students learn to visualize data through histograms and cumulative distribution plots, which help in understanding the distribution of service times and other datasets. The instructor discusses the significance of measures of central tendency, including mean, median, and mode, and how they relate to data analysis. Outliers and their impact on statistical measures are also covered, along with techniques for detecting them. The lecture concludes with a discussion on the advantages and disadvantages of different data visualization methods, preparing students for practical applications in their future analyses.

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Instructor

Vivek Subramanian

Teaching & PhD PhD Students Giovanni Ruffolo, Giada Romano, Sanjay Manoharan, Kyle Haas, Claude Dahan, Biruktait Ayele Lemecho, Yagmur Ceren Alatas, Tugçe Delipinar Past EPFL PhD Students Amin Hodaei, Mustafa Mohieldin Fadlelmula Fadlelseed Past EPFL PhD Students as codirector Mohammad Jafarpour Courses Organic and printed electronics MICRO-505 This course addresses the implementation of organic and printed electronics technologies using large area manufacturing techniques. It will provide

Official source

Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics

Electrical engineering

Telecommunications: Modulation

Related concepts (32)

Probability distribution

In probability theory and statistics, a probability distribution is the mathematical function that gives the probabilities of occurrence of different possible outcomes for an experiment. It is a mathematical description of a random phenomenon in terms of its sample space and the probabilities of events (subsets of the sample space). For instance, if X is used to denote the outcome of a coin toss ("the experiment"), then the probability distribution of X would take the value 0.5 (1 in 2 or 1/2) for X = heads, and 0.

Frequency (statistics)

In statistics, the frequency or absolute frequency of an event is the number of times the observation has occurred/recorded in an experiment or study. These frequencies are often depicted graphically or in tabular form. The cumulative frequency is the total of the absolute frequencies of all events at or below a certain point in an ordered list of events. The relative frequency (or empirical probability) of an event is the absolute frequency normalized by the total number of events: The values of for all events can be plotted to produce a frequency distribution.

Mean

There are several kinds of mean in mathematics, especially in statistics. Each mean serves to summarize a given group of data, often to better understand the overall value (magnitude and sign) of a given data set. For a data set, the arithmetic mean, also known as "arithmetic average", is a measure of central tendency of a finite set of numbers: specifically, the sum of the values divided by the number of values. The arithmetic mean of a set of numbers x1, x2, ..., xn is typically denoted using an overhead bar, .

Type theory

In mathematics, logic, and computer science, a type theory is the formal presentation of a specific type system, and in general, type theory is the academic study of type systems. Some type theories serve as alternatives to set theory as a foundation of mathematics. Two influential type theories that were proposed as foundations are Alonzo Church's typed λ-calculus and Per Martin-Löf's intuitionistic type theory. Most computerized proof-writing systems use a type theory for their foundation, a common one is Thierry Coquand's Calculus of Inductive Constructions.

Probability

Probability is the branch of mathematics concerning numerical descriptions of how likely an event is to occur, or how likely it is that a proposition is true. The probability of an event is a number between 0 and 1, where, roughly speaking, 0 indicates impossibility of the event and 1 indicates certainty. The higher the probability of an event, the more likely it is that the event will occur. A simple example is the tossing of a fair (unbiased) coin.

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