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BSc.CSIT Introduction to Information Technology C Programming Digital Logic Mathematics I (Calculus) Physics Discrete Structures Object Oriented Programming Microprocessor Statistics I Mathematics II Data Structures and Algorithms Numerical Method Computer Architecture Computer Graphics Statistics II Theory of Computation Computer Networks Operating Systems Database Management System Artificial Intelligence Multimedia Computing Web Technology System Analysis and Design Wireless Networking Microprocessor Based Design Society and Ethics in Information Technology Knowledge Management Design and Analysis of Algorithms Simulation and Modelling Image Processing Cryptography Software Engineering Compiler Design and Construction E-Governance NET Centric Computing Technical Writing Applied Logic E-commerce Automation and Robotics Neural Networks Computer Hardware Design Cognitive Science Advanced Java Programming Data Warehousing and Data Mining Principles of Management Project Work Information Retrieval Database Administration Software Project Management Network Security Digital System Design Network and System Administration International Marketing Advanced Database Internship Advanced Networking with IPv6 Distributed Networking Game Technology Distributed and Object Oriented Database Introduction to Cloud Computing Geographical Information System Decision Support System and Expert System Mobile Application Development Embedded Systems Programming International Business Management
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Introduction

Basic concept of statistics Application of Statistics in the field of Computer Science & Information technology Scales of measurement Variables Types of Data Notion of a statistical population

Descriptive Statistics

Measures of central tendency Measures of dispersion Measures of skewness Measures of kurtosis Moments Steam and leaf display Five number summary Box plot Problems and illustrative examples related to computer Science and IT

Introduction to Probability

Concepts of probability Definitions of probability Laws of probability Bayes theorem Prior and posterior probabilities Problems and illustrative examples related to computer Science and IT

Sampling

Definitions of population Sample survey vs. census survey Sampling error and non-sampling error Types of sampling

Random Variables and Mathematical Expectation

Concept of a random variable Types of random variables Probability distribution of a random variable Mathematical expectation of a random variable Addition and multiplicative theorems of expectation Problems and illustrative examples related to computer Science and IT

Probability Distributions

Probability distribution function Joint probability distribution of two random variables Discrete distributions: Bernoulli trial, Binomial and Poisson distributions Continuous distribution: Normal distributions Standardization of normal distribution Normal distribution as an approximation of Binomial and Poisson distribution Exponential, Gamma distribution Problems and illustrative examples related to computer Science and IT

Correlation and Linear Regression

Bivariate data Bivariate frequency distribution Correlation between two variables Karl Pearson’s coefficient of correlation(r) Spearman’s rank correlation Regression Analysis: Fitting of lines of regression by the least squares method Coefficient of determination Problems and illustrative examples related to computer Science and IT

Statistics I

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Introduction

A computer is an electronic device that accepts data as input, processes it, and produces meaningful output as a result.

A computer is an electronic device, operating under the control of instructions stored in its own memory, that can accept data, process the data according to specified rules, produce results, and store the results for future use.

Digital and Analog Computers

Digital Computer

A digital computer operates using binary digits (0s and 1s) to process data through mathematical and logical operations. It's a versatile tool utilized across diverse fields for tasks ranging from basic calculations to complex simulations and data analysis. Example of these computers are IBMPC, Apple/Macintosh etc.

Analog Computer

An analog computer operates on continuous data like length or voltage, using continuous signals. Unlike digital computers, it doesn't rely on exact values but approximations. Widely used in scientific and industrial fields, they excel in solving differential equations and represent physical quantities through waves. Examples include the speedometer, thermometer, barometer, lactometer, and seismograph.

Difference between analog and digital computer

Analog computer Digital computer
These computers work with physical values such as temperature, pressure, etc. These Computers work with binary digits (0s, 1s)
These computers are based on continuous data. These computers are based on discrete data.
It has very low accuracy. It has high accuracy.
Based on similarity measurement principle. Based on counting principle.
They are faster than digital computers. Slower than analog computers.
It has no or limited storage capacity. It has high storage capacity.
It does a single-purpose job. It does a multi-purpose job.
No possibility of reprogramming. It can be reprogrammed.
The cost is low and portable. The cost is high and not easily portable.
Analog signal processing can be done in real time and consumes less bandwidth. There is no guarantee that digital signal processing can be done in real time and consumes more bandwidth to carry out the same information.

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