Skewness and Kurtosis- Introduction- Skewness and Kurtosis are very important concepts in statistics and have several applications. In addition, they characterize the nature of data distribution which make data analysis easier. Moreover, I will separately discuss skewness and kurtosis in further sections. Skewness- Skewness refers the measurement of lack of symmetry in data distribution. Measures […]
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Measures of central tendency in statistics refers to a value which characterizes all the the data. Mean, median and mode are very important measures of central tendency. Measures of central tendency is very fundamental in data science, machine learning and data analytics areas. Moreover, if you want to make a carrier in data analytics you
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Frequency distribution in statistics refers to a graph or table which depicts or illustrate the occurrences of values. Frequency distribution is very important in study of statistics, machine learning and data science area. To understand frequency distribution you have to understand organization of data. Basically, there are three types of data organization techniques. 1- Individual
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UNIVERSITY GRANTS COMMISSION NET BUREAU NET SYLLABUS Subject : COMPUTER SCIENCE AND APPLICATIONS Code No.:(87) Unit – 1 : Discrete Structures and Optimization Mathematical Logic: Propositional and Predicate Logic, Propositional Equivalences, Normal Forms, Predicates and Quantifiers, Nested Quantifiers, Rules of Inference. Sets and Relations: Set Operations, Representation and Properties of Relations, Equivalence Relations, Partially Ordering.
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CSIR-UGC National Eligibility Test (NET) for Junior Research Fellowship and Lecturer-ship COMMON SYLLABUS FOR PART ‘B’ AND ‘C’ MATHEMATICAL SCIENCES UNIT – 1 Analysis: Elementary set theory, finite, countable and uncountable sets, Real number system as a complete ordered field, Archimedean property, supremum, infimum. Sequences and series, convergence, limsup, liminf. Bolzano Weierstrass theorem, Heine Borel
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Vector Space- A set V is called vector space on which two operations are defined. 1- Vector Addition 2- Scalar Multiplication Further, vector addition must follow the following properties and laws for vector addition. 1- Closure Property If u and v are two vectors in V then u+v must be in V. 2- Commutative Law
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To understand random variable first you have to know about events. I will make you understand using examples. What are events? Example Tossing three coins on which one head turns up {HT,HH} A random variable quantify events of occurence. In other words, a random variable X is a function from set of events to real
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Mutually Exclusive Events- Two or more events events are said to be mutually exclusive if only one can happen at a time. Example-1 In tossing a coin, event of tail up (T) and even of heads up (H) can not happen simultaneously. They are mutually exclusive events. Example-2 In rolling of a dice, event of
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Linear Independence of Vectors Suppose α1, α2, α3, α4…………αn are vectors of V(F) where F is field. And there exist scalers a1, a2, a3, a4………..an which belong to field F. α1, α2, α3, α4…………αn vectors are called lineary independent if a1 α1 + a2 α2 + a3 α3+ ……… + an αn = 0 and
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Ubuntu only provides an iso image of the operating system and you need to make a pen drive bootable to install ubuntu. I will show step-by-step how to make a pen drive bootable using USB Installer. Step-1 Download USB installer using this link https://universal-usb-installer.en.uptodown.com/windows and keep in pendrive. Step-2 Download Ubuntu operating system using this
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