كلية العلوم والدراسات النظرية

This course introduces the student to statistics with business applications. The course covers both descriptive and inferential statistics. The purpose of this course is to introduce the basic statistical methods used in Business, IT applications and other related multidisciplinary areas. Students will learn how to select and apply appropriate statistical methods to analyze data from clinical trials, and how to present, interpret and discuss the analyses clearly and concisely. Topics included are measures of central tendency; measures of dispersion; graphical displays of data; linear regression; basic probability concepts; binomial and normal probability distributions; confidence intervals; and hypothesis testing of mean, proportion for one or two populations. The course also covers ANOVA and hypothesis tests for Goodness of Fit. By the end of this module, students should be able to apply the concepts of statistics to a business situation, the concepts of discrete and normal probability distributions, to formulate testing of hypotheses in constructing and interpreting confidence intervals, to analyze data sets using linear regression and correlation and to interpret the results obtained from analyzing data using software.

Topics included are measures of central tendency; measures of dispersion; graphical displays of data; linear regression; basic probability concepts; binomial and normal probability distributions; confidence intervals; and hypothesis testing of mean, proportion for one or two populations. The course also covers ANOVA and hypothesis tests for Goodness of Fit. By the end of this module, students should be able to apply the concepts of statistics to a business situation, the concepts of discrete and normal probability distributions, to formulate testing of hypotheses in constructing and interpreting confidence intervals, to analyze data sets using linear regression and correlation and to interpret the results obtained from analyzing data using software.

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This course addresses the importance of applying quantitative methods and analysis to the solution of business problems using structured problem solving and specialized data analysis software tools. The main focus of the course is on solutions to problems of inefficiency, poor productivity, and risky situations within the management of business and technical processes, projects, and operations. Some of the methodologies covered are linear programming, PERT/CPM analysis, time series, decision tree analysis, and data mining. Upon completion of this module, students should be able to recognize various decision-making options based on probability and risk. Predict data trends based on historical or variable information. Manipulate the balance between waiting line cost and service cost. Calculate the solutions for linear programming problems. Construct various inventory controls and project management models. Use data for simulation modelling and appraise the outcomes.

Topics included are Introduction to Quantitative Analysis; Decision Analysis; Forecasting;  Regression Models; Waiting Lines and Queuing Theory Models;  Linear Programming Models: Graphical and Computer Method. The course also covers Linear Programming Applications, Transportation and Assignment Models. Moreover, Inventory Control Models, Project Management, and Simulation Modeling.

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This course in discrete mathematics provides the mathematical background needed for all subsequent courses in computer science and for all subsequent courses in the many branches of discrete mathematics. This course introduces students to fundamental algebraic, logical and combinatorial concepts in mathematics. Topics include Boolean Logic, Predicate Logic, sets, mapping, relations, elementary counting principles, algorithm & proof techniques, graphs, and recursions. Upon completion of this module, students will be able to understand and use (abstract) discrete structures that are backbones of computer science. Explain competently the concept of Logic and Boolean Algebra. Analyze the Basic Structures of Discrete Mathematics, such as Sets, Functions, Sequences, Sums, and Matrices. Calculate the counting problems and general problems using Algorithms. Explain accurately the concept of modular arithmetic and linear congruences. Illustrate the concept of Graph Theory in " Graphs", "Trees" and "Relations". Judge correctly the proof of statements by Mathematical Induction and concept of Recursion.

Topics include Boolean Logic, Predicate Logic, sets, mapping, relations, elementary counting principles, algorithm & proof techniques, graphs, and recursions. Upon completion of this module, students will be able to understand and use (abstract) discrete structures that are backbones of computer science. Explain competently the concept of Logic and Boolean Algebra. Analyze the Basic Structures of Discrete Mathematics, such as Sets, Functions, Sequences, Sums, and Matrices. Calculate the counting problems and general problems using Algorithms. Explain accurately the concept of modular arithmetic and linear congruences. Illustrate the concept of Graph Theory in " Graphs", "Trees" and "Relations". Judge correctly the proof of statements by Mathematical Induction and concept of Recursion.

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This course of Linear Algebra is most widely used in the engineering core subjects, and other fields. The course offers the solution of systems of algebraic equations obtained from engineering problems and eigen-system analysis, a range of ways for the students to develop their skills and knowledge by introducing several specialized areas of mathematics and its applications in engineering. The main topics include in this course are systems of linear equations, their applications and solutions. Matrices, vectors, elementary operations on vectors, linear independence, spanning sets, and bases. Eigenvalues, eigenvectors, and Eigen spaces will be discussed. Example and applications will be primarily based on IT systems. Upon completion of this module, students will be able to recognize methods to solve a system of linear equations. Describe a geometric technique for maximizing or minimizing a linear expression. Calculate the dot product and the cross product of vectors, in addition to define the Diagonalization and Quadratic Forms. Analyze the properties of vector spaces and subspaces using linear transformations. Illustrate the properties of matrices such as invariability, determinant, etc. Clarify the concept of the eigenvectors, eigenvalues and linear transformation.

The main topics include in this course are systems of linear equations, their applications and solutions. Matrices, vectors, elementary operations on vectors, linear independence, spanning sets, and bases. Eigenvalues, eigenvectors, and Eigen spaces will be discussed. Example and applications will be primarily based on IT systems. Upon completion of this module, students will be able to recognize methods to solve a system of linear equations. Describe a geometric technique for maximizing or minimizing a linear expression. Calculate the dot product and the cross product of vectors, in addition to define the Diagonalization and Quadratic Forms. Analyze the properties of vector spaces and subspaces using linear transformations. Illustrate the properties of matrices such as invariability, determinant, etc. Clarify the concept of the eigenvectors, eigenvalues and linear transformation.

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This course will provide the fundamental ideas of physics. Beginning with kinematics, it includes motion in one and two dimensions, Newton’s laws of motion and their applications, work and energy, linear momentum and collisions, rotational motion, and principles of conservation. Additionally, a study of electric charges, forces, and field, Coulomb’s law. The purpose of this course is to identify the basic physical quantities, explain the concepts and apply the basic knowledge of physics necessary for their specialization programs. After successful completion of this course, students will be able to state basic concepts of mechanics and electrostatics theoretically and mathematically. State suitable theories related to the given problems. Demonstrate numerical skills to solve different type of problems in kinematics and electrostatics.

Students will learn the fundamental ideas of physics. Beginning with kinematics, it includes motion in one and two dimensions, Newton’s laws of motion and their applications, work and energy, linear momentum and collisions, rotational motion, and principles of conservation. Additionally, a study of electric charges, forces, and field, Coulomb’s law.

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This course will provide a study of electric potential and electric potential energy, electric current, electric circuits, magnetism, thermal physics, transfer of energy in thermal processes, the laws of thermodynamics, vibrations and waves, periodic motion, oscillations, the motion of a pendulum, sound waves, electromagnetic waves, the nature of light, and reflection and refraction of light. The main purpose of this course is to identify and explain the concepts and apply the basic knowledge of physics (related to electrostatics, electricity and magnetisms, heat, thermodynamics, oscillations, waves, electromagnetic waves, reflection and refraction of light) necessary for their specialization programs. After successful completion of this course, students will be able to state and explain the basic concepts of electrostatics, electricity, magnetism, thermodynamics, sound and light theoretically and mathematically. Demonstrate numerical skills to solve different type of problems in electrostatics, electricity, magnetism, thermodynamics, sound and light.

This course will provide a study of electric potential and electric potential energy, electric current, electric circuits, magnetism, thermal physics, transfer of energy in thermal processes, the laws of thermodynamics, vibrations and waves, periodic motion, oscillations, the motion of a pendulum, sound waves, electromagnetic waves, the nature of light, and reflection and refraction of light.

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This course introduces data science students to statistics and probabilities. The course covers both descriptive and inferential statistics. Topics included are: measures of central location; measures of variability; graphical displays of data; linear regression; basic probability concepts; binomial and normal probability distributions; confidence intervals; and hypothesis testing of the mean and proportion for one or two populations. The course also covers ANOVA and hypothesis tests for goodness of fit. Key success factors in the course will be for the student to build on statistical techniques and spreadsheet tools covered in prerequisite(s) courses.

1. Graphical displays of data.
2. Measures of central location and measures of variability.
3. Basic probability concepts.
4. Binomial and normal probability distributions.
5. Confidence intervals.
6. Hypothesis testing of the mean and proportion for one or two populations.
7. Correlation and linear regression.
8. ANOVA and hypothesis tests for goodness of fit.

Mario F. Triola (2011). Elementary Statistics Using the TI-83/84 Plus Calculator. (3rd edition). Addison-Wesley, Pearson Education. ISBN: 978-0-321-64148-9.

This calculus course provides a robust foundation in mathematical principles and their practical applications. From fundamental concepts like functions, limits, and continuity to advanced topics such as derivatives, integration, and techniques like substitution and the fundamental theorem, the curriculum is designed to empower students with a comprehensive understanding. The course delves into advanced subjects like infinite series, parametric and polar curves, conic sections, and vectors in three-dimensional space. By maintaining a balance between theory and application, students are well-prepared for academic excellence and adept problem-solving in real-world scenarios.

1. Function and models
2. Limits and Derivatives
3. Differentiation Rules
4. Applications of Differentiation
5. Integrals
6. Application of Integrals
7. Sequences and Series
8. 3-D Vectors

This course introduces students to fundamental algebraic, logical and combinatorial concepts in mathematics. Topics include Boolean Logic, Predicate Logic, sets, mapping, relations, elementary counting principles, algorithm & proof techniques, graphs, and recursions

1. Logic theory – Boolean logic & predicate logic
2. Fundamental structures (sets, functions, sequences & sums)
3. Proof techniques (induction, recursion)
4. Basic counting
5. Graph theory
6. Basics of algorithms, growth functions, complexity

This course introduces the student to statistics with business applications. The course covers both descriptive and inferential statistics. Topics included are: measures of central tendency; measures of dispersion; graphical displays of data; linear regression; basic probability concepts; binomial and normal probability distributions; confidence intervals; and hypothesis testing of mean, proportion for one or two populations. The course also covers ANOVA and hypothesis tests for Goodness of Fit. These topics will be covered using a basic knowledge of algebra and Microsoft Excel.

1. Vocabulary and Graphical Displays
2. Numerical Descriptive Statistics
3. Probability
4. Discrete Probability Distributions
5. Continuous Distributions and Central Limit Theorem
6. Estimation and Confidence Intervals
7. Hypothesis Testing of the Parameter
8. Hypothesis Testing Using Samples from Two Populations
9. Correlation and Linear Regression
10. Chi-Square Tests
11. Analysis of variance (ANOVA)

يقدم هذا المقرر المفاهيم الرياضية الأساسية التي يحتاجها طلبة العلوم والدراسات النظرية خلال دراستهم الجامعية. 

ويتضمن المقرر المواضيع التالية:

المجموعات وجبر المجموعات، الأعداد الحقيقية وخواصها، القوى والأسس، العبارات الجبرية والعمليات عليها، المعادلات الخطية والمتباينات الخطية (المتراجحات) بمجهول واحد، المعادلات والمتباينات التي تحوي القيمة المطلقة، حل نظام مكون من معادلتين خطيتين بمتغيرين، حل معادلات الدرجة الثانية بمجهول واحد، الهندسة التحليلية (المستوى الديكارتي -الخط المستقيم ميله ومعادلته ورسمه)، تحليل كثيرات الحدود، الدوال، المتتاليات.

This course will address the outcomes of introductory and intermediate algebra. 

Basic algebraic properties, integers, simplifying and factoring polynomials, solving and graphing linear equations and inequalities, solving systems of equations in two variables, functions, rational expressions, quadratic and rational equations and inequalities, absolute value, graphing systems of equations and inequalities, and other selected topics. Applications will be emphasized, and numeric, algebraic, and graphical modes will be used.