The document describes fitting a quadratic model to a set of (x,y) data points. It shows the process of setting up and solving a system of equations to determine the coefficients a, b, and c in the quadratic function y = ax^2 + bx + c. The system of equations is obtained by setting the quadratic formula equal to the y-value for each data point. The document solves for the coefficients step-by-step to find that the quadratic model for the given data is y = 2x^2 + 2x - 3.
The document provides examples of modeling data with polynomials. Example 1 shows data of distance traveled by a ball down an inclined plane over time. A quadratic polynomial model is found to fit this data, with the formula d = 3t^2, where d is distance and t is time. Example 2 shows additional data over time and x values, to be fitted with a polynomial model.
This document provides examples and instructions for multiplying monomials using the rules of exponents. It begins with an essential question about how to multiply monomials using exponents. It then provides the rules: add/subtract like terms and multiply like parts including numbers and variables. Several examples are worked through step-by-step to multiply monomials like -2xy, 3xy(-4xy)^3, and 7x(7x). The last example involves multiplying monomials, 4xy^2 and 8y^3, to determine how much money Jeff made from stock dividends. Homework problems from the book are assigned.
The document discusses exponential and natural logarithm functions. It provides examples of using exponential functions to calculate continuous compound interest on investments over time, and shows that continuous compounding yields slightly higher returns. It also discusses properties of the natural logarithm function and its relationship to the exponential function. An example calculates the area under a curve bounded by lines using the natural logarithm formula.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms.
The document discusses probability theory and concepts like sample space, outcomes, events, and the probability of events occurring. It provides examples of calculating probabilities, including rolling dice. The key points are:
- Probability theory is the study of chance using mathematics
- An experiment is a situation with possible results called outcomes
- The sample space includes all possible outcomes
- An event is a subset of outcomes of interest within the sample space
- Probability is calculated as the number of favorable outcomes divided by the total number of possible outcomes
- Examples are provided to demonstrate calculating probabilities, such as the probability of rolling a 7 when rolling two fair dice.
The document discusses solving equations with radicals by working through examples of solving various equations with radicals. It demonstrates taking square roots and cube roots of both sides of equations to solve for variables. It also discusses the concept of extraneous solutions that may arise when solving equations with radicals.
The document shows examples of advanced factoring techniques including factoring by grouping, factoring quadratics, and factoring a polynomial into linear factors in order to graph the solution set. It provides step-by-step workings to factor expressions into their simplest linear factors in order to determine possible solutions for equations.
The document discusses finite differences and polynomial functions. It is shown that if the nth differences of a function are equal, the function is a polynomial of degree n. The document provides examples of using difference tables to determine if a function is polynomial and, if so, its degree. It is concluded that applying the polynomial difference theorem involves examining differences in a table to determine if the data represents a polynomial function.
The document provides examples of modeling data with polynomials. Example 1 shows data of distance traveled by a ball down an inclined plane over time. A quadratic polynomial model is found to fit this data, with the formula d = 3t^2, where d is distance and t is time. Example 2 shows additional data over time and x values, to be fitted with a polynomial model.
This document provides examples and instructions for multiplying monomials using the rules of exponents. It begins with an essential question about how to multiply monomials using exponents. It then provides the rules: add/subtract like terms and multiply like parts including numbers and variables. Several examples are worked through step-by-step to multiply monomials like -2xy, 3xy(-4xy)^3, and 7x(7x). The last example involves multiplying monomials, 4xy^2 and 8y^3, to determine how much money Jeff made from stock dividends. Homework problems from the book are assigned.
The document discusses exponential and natural logarithm functions. It provides examples of using exponential functions to calculate continuous compound interest on investments over time, and shows that continuous compounding yields slightly higher returns. It also discusses properties of the natural logarithm function and its relationship to the exponential function. An example calculates the area under a curve bounded by lines using the natural logarithm formula.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms.
The document discusses probability theory and concepts like sample space, outcomes, events, and the probability of events occurring. It provides examples of calculating probabilities, including rolling dice. The key points are:
- Probability theory is the study of chance using mathematics
- An experiment is a situation with possible results called outcomes
- The sample space includes all possible outcomes
- An event is a subset of outcomes of interest within the sample space
- Probability is calculated as the number of favorable outcomes divided by the total number of possible outcomes
- Examples are provided to demonstrate calculating probabilities, such as the probability of rolling a 7 when rolling two fair dice.
The document discusses solving equations with radicals by working through examples of solving various equations with radicals. It demonstrates taking square roots and cube roots of both sides of equations to solve for variables. It also discusses the concept of extraneous solutions that may arise when solving equations with radicals.
The document shows examples of advanced factoring techniques including factoring by grouping, factoring quadratics, and factoring a polynomial into linear factors in order to graph the solution set. It provides step-by-step workings to factor expressions into their simplest linear factors in order to determine possible solutions for equations.
The document discusses finite differences and polynomial functions. It is shown that if the nth differences of a function are equal, the function is a polynomial of degree n. The document provides examples of using difference tables to determine if a function is polynomial and, if so, its degree. It is concluded that applying the polynomial difference theorem involves examining differences in a table to determine if the data represents a polynomial function.
The document discusses sample spaces and theoretical probability. It defines key terms like event, sample space, tree diagram, and theoretical vs experimental probability. It provides examples of using tree diagrams and the fundamental counting principle to determine the sample space and theoretical probability of outcomes for situations like making sandwiches or tossing coins. The probability of getting exactly two heads when tossing three coins is 3/8.
This document discusses key concepts for fitting a line to scatterplot data including:
- A scatterplot is a collection of discrete data points that describe a situation.
- A line of best fit/regression line is a line that comes close to most of the points in a scatterplot but does not need to touch any points.
- The coefficient of correlation determines the strength of the relationship between variables on a scale of -1 to 1, where values closer to 1 or -1 indicate a stronger correlation and the sign of the value indicates the slope of the line of best fit.
- Two examples are provided to demonstrate positive correlation, calculating the correlation value r, and using the line of best fit to predict expected values
The document shows the step-by-step work to solve two inverse variation problems. In the first problem, it is given that y=563 when x=3, and the question is to find y when x=9. Through substituting values into the inverse variation equation y=kx^2 and solving for k, it is determined that y=567 when x=9. In the second part of the problem, it is asked to find y when x=5, which is determined to be 175. The second problem finds g when h=9, given that g=3 when h=6, determining that g=2 when h=9.
The document discusses composite functions and examples of evaluating composite functions. It begins with the definition of a composite function as a function that maps x onto g(f(x)), where the domain is all values in the domain of f that are also in the domain of g. It then provides examples of evaluating composite functions by first applying the inner function f and then applying the outer function g. It finds domains of composite functions and evaluates several examples of composite functions.
The document discusses solving equations involving squares and square roots. It provides examples of solving equations with squares and square roots, including solving for unknown variables and checking solutions. Key steps shown include taking the square root of both sides of an equation, squaring terms, and isolating the variable. Applications mentioned include physics, engineering, and mechanics.
The document discusses factoring quadratic trinomials and polynomials that are not easily factored. It provides examples of factoring quadratic expressions using the factors of ac and the quadratic formula. In one example, it factors the expression m^2 + 2m - 6399 by first finding the roots with the quadratic formula, then using the factor theorem to write the factored form as (m - 79)(m + 81). In another example, it factors the expression 20x^2 - 53x + 12 by finding two terms whose sum is the middle term, then grouping the expression accordingly.
This document defines key terms related to lines of best fit, including observed and predicted values, errors, the line of best fit, method of least squares, and center of gravity. It then provides an example problem involving finding the line of best fit for beef prices at different lean percentages and using the line to predict prices for 57% and 87% lean beef. The document instructs the reader to complete related homework problems.
This document discusses power functions and exponents. It defines power functions as operations where a base is taken to an exponent. It provides examples of squaring (x^2), cubing (x^3), and fourth power (x^4) functions. Key properties discussed include that power functions go through the origin, have all real numbers as their domain, and their range depends on whether the exponent is odd or even. Symmetry properties also depend on the exponent. Examples are provided to illustrate calculating probabilities using exponents.
The document provides examples for solving and graphing inequalities on a number line. It defines solving an inequality as finding all values that make the inequality true. It also covers the addition, multiplication, and division properties of inequalities. An example problem solves and graphs the inequalities 7 - n ≤ 5 and 13x - 4 > 22, demonstrating each step of the process.
This document discusses permutations and combinations of letters. It asks the reader to list all permutations of 2 letters taken from the letters P, O, W, E, and R, which are provided. It then asks how many groups would exist if those permutations that are the same letters arranged in a different order, such as OW and WO, are placed into the same group.
1. An inverse function undoes the operations of the original function by switching the x and y values.
2. The domain of the inverse function is the range of the original function, and the range of the inverse is the domain of the original.
3. Inverse functions are found by solving the original equation for y and then switching x and y. When applying the inverse function after the original, the output should be the original input.
The document defines and provides examples of angle relationships including adjacent angles, linear pairs, vertical angles, complementary angles, and supplementary angles. It defines each term and provides examples of identifying angle pairs that satisfy each relationship. It also includes examples of using properties of these angle relationships to solve problems, such as finding missing angle measures.
The document defines various terms related to angle measure including ray, angle, vertex, acute angle, obtuse angle, and angle bisector. It then provides examples measuring angles in a figure and solving an equation involving angle measures.
This document discusses finding points and midpoints on line segments. It defines midpoint as the point halfway between two endpoints and provides the formula to calculate it. Several examples are given to demonstrate how to find the midpoint of a segment, locate a point at a fractional distance from one endpoint, and find a point where the ratio of distances from the endpoints is a given ratio. The key concepts covered are calculating midpoints using averages of x- and y-coordinates, and setting up and solving equations to locate interior points using fractional or ratio distances along a segment.
This document defines key vocabulary terms related to line segments and distance. It defines a line segment as a portion of a line distinguished by endpoints, and defines betweenness of points and the term "between." It also defines congruent segments, constructions, distance, and irrational numbers. Several examples are provided to demonstrate calculating distances between points on a number line, using a ruler to measure segments, and applying the Pythagorean theorem.
This document defines key vocabulary terms related to line segments and distance, including line segment, betweenness of points, congruent segments, and distance formula. It provides examples of calculating distances between points on number lines and using the Pythagorean theorem to find distances between points graphed on a coordinate plane. Examples include measuring line segments with a ruler, finding distances by adding or subtracting measures, and applying the distance formula and Pythagorean theorem to solve for unknown distances.
This document introduces basic geometry concepts such as points, lines, planes, and their intersections. It defines a point as having no size or shape, a line as an infinite set of collinear points, and a plane as a flat surface extending indefinitely. Examples demonstrate identifying geometric shapes from real-world objects and graphing points and lines on a coordinate plane. The summary defines key terms and provides examples of geometric concepts and relationships.
The document discusses inverse functions and relations. It defines an inverse relation as one where the coordinates of a relation are switched, and an inverse function as one where the domain and range of a function are switched. It provides examples of finding the inverse of specific relations and functions by switching their coordinates or domain and range. It also discusses how to determine if two functions are inverses using their graphs and the horizontal line test.
The document discusses composition of functions. It defines composition of functions as using the output of one function as the input of another. It provides an example of composing two functions f and g, showing the steps of evaluating f(g(x)) and g(f(x)) at different values of x. Another example is given with two functions defined by sets of ordered pairs, finding the compositions f∘g and g∘f by evaluating them at different inputs and stating their domains and ranges.
The document discusses operations that can be performed on functions, including addition, subtraction, multiplication, and division. Definitions of each operation are provided, along with examples of applying the operations to specific functions. Addition of functions involves adding the outputs of each function, subtraction involves subtracting the outputs, multiplication involves multiplying the outputs, and division involves dividing the outputs given the denominator function is not equal to 0. Several examples are worked through applying the different operations to functions like f(x)=2x and g(x)=-x+5. The examples also demonstrate evaluating composite functions and restricting domains as needed.
The document discusses determining the number and type of roots of polynomial equations. It states that every polynomial with degree greater than zero has at least one root in the set of complex numbers according to the Fundamental Theorem of Algebra. Descartes' Rule of Signs is introduced, which relates the number of changes in sign of a polynomial's terms to its possible positive and negative real roots. An example problem is worked through applying these concepts to determine the possible number of positive, negative, and imaginary roots.
This document discusses synthetic division and the remainder and factor theorems. It provides examples of using synthetic division to evaluate functions, determine the number of terms in a sequence, and factor polynomials. The key steps of synthetic division are shown, along with checking the remainder and determining common factors. Three examples are worked through to demonstrate these concepts.
The document discusses sample spaces and theoretical probability. It defines key terms like event, sample space, tree diagram, and theoretical vs experimental probability. It provides examples of using tree diagrams and the fundamental counting principle to determine the sample space and theoretical probability of outcomes for situations like making sandwiches or tossing coins. The probability of getting exactly two heads when tossing three coins is 3/8.
This document discusses key concepts for fitting a line to scatterplot data including:
- A scatterplot is a collection of discrete data points that describe a situation.
- A line of best fit/regression line is a line that comes close to most of the points in a scatterplot but does not need to touch any points.
- The coefficient of correlation determines the strength of the relationship between variables on a scale of -1 to 1, where values closer to 1 or -1 indicate a stronger correlation and the sign of the value indicates the slope of the line of best fit.
- Two examples are provided to demonstrate positive correlation, calculating the correlation value r, and using the line of best fit to predict expected values
The document shows the step-by-step work to solve two inverse variation problems. In the first problem, it is given that y=563 when x=3, and the question is to find y when x=9. Through substituting values into the inverse variation equation y=kx^2 and solving for k, it is determined that y=567 when x=9. In the second part of the problem, it is asked to find y when x=5, which is determined to be 175. The second problem finds g when h=9, given that g=3 when h=6, determining that g=2 when h=9.
The document discusses composite functions and examples of evaluating composite functions. It begins with the definition of a composite function as a function that maps x onto g(f(x)), where the domain is all values in the domain of f that are also in the domain of g. It then provides examples of evaluating composite functions by first applying the inner function f and then applying the outer function g. It finds domains of composite functions and evaluates several examples of composite functions.
The document discusses solving equations involving squares and square roots. It provides examples of solving equations with squares and square roots, including solving for unknown variables and checking solutions. Key steps shown include taking the square root of both sides of an equation, squaring terms, and isolating the variable. Applications mentioned include physics, engineering, and mechanics.
The document discusses factoring quadratic trinomials and polynomials that are not easily factored. It provides examples of factoring quadratic expressions using the factors of ac and the quadratic formula. In one example, it factors the expression m^2 + 2m - 6399 by first finding the roots with the quadratic formula, then using the factor theorem to write the factored form as (m - 79)(m + 81). In another example, it factors the expression 20x^2 - 53x + 12 by finding two terms whose sum is the middle term, then grouping the expression accordingly.
This document defines key terms related to lines of best fit, including observed and predicted values, errors, the line of best fit, method of least squares, and center of gravity. It then provides an example problem involving finding the line of best fit for beef prices at different lean percentages and using the line to predict prices for 57% and 87% lean beef. The document instructs the reader to complete related homework problems.
This document discusses power functions and exponents. It defines power functions as operations where a base is taken to an exponent. It provides examples of squaring (x^2), cubing (x^3), and fourth power (x^4) functions. Key properties discussed include that power functions go through the origin, have all real numbers as their domain, and their range depends on whether the exponent is odd or even. Symmetry properties also depend on the exponent. Examples are provided to illustrate calculating probabilities using exponents.
The document provides examples for solving and graphing inequalities on a number line. It defines solving an inequality as finding all values that make the inequality true. It also covers the addition, multiplication, and division properties of inequalities. An example problem solves and graphs the inequalities 7 - n ≤ 5 and 13x - 4 > 22, demonstrating each step of the process.
This document discusses permutations and combinations of letters. It asks the reader to list all permutations of 2 letters taken from the letters P, O, W, E, and R, which are provided. It then asks how many groups would exist if those permutations that are the same letters arranged in a different order, such as OW and WO, are placed into the same group.
1. An inverse function undoes the operations of the original function by switching the x and y values.
2. The domain of the inverse function is the range of the original function, and the range of the inverse is the domain of the original.
3. Inverse functions are found by solving the original equation for y and then switching x and y. When applying the inverse function after the original, the output should be the original input.
The document defines and provides examples of angle relationships including adjacent angles, linear pairs, vertical angles, complementary angles, and supplementary angles. It defines each term and provides examples of identifying angle pairs that satisfy each relationship. It also includes examples of using properties of these angle relationships to solve problems, such as finding missing angle measures.
The document defines various terms related to angle measure including ray, angle, vertex, acute angle, obtuse angle, and angle bisector. It then provides examples measuring angles in a figure and solving an equation involving angle measures.
This document discusses finding points and midpoints on line segments. It defines midpoint as the point halfway between two endpoints and provides the formula to calculate it. Several examples are given to demonstrate how to find the midpoint of a segment, locate a point at a fractional distance from one endpoint, and find a point where the ratio of distances from the endpoints is a given ratio. The key concepts covered are calculating midpoints using averages of x- and y-coordinates, and setting up and solving equations to locate interior points using fractional or ratio distances along a segment.
This document defines key vocabulary terms related to line segments and distance. It defines a line segment as a portion of a line distinguished by endpoints, and defines betweenness of points and the term "between." It also defines congruent segments, constructions, distance, and irrational numbers. Several examples are provided to demonstrate calculating distances between points on a number line, using a ruler to measure segments, and applying the Pythagorean theorem.
This document defines key vocabulary terms related to line segments and distance, including line segment, betweenness of points, congruent segments, and distance formula. It provides examples of calculating distances between points on number lines and using the Pythagorean theorem to find distances between points graphed on a coordinate plane. Examples include measuring line segments with a ruler, finding distances by adding or subtracting measures, and applying the distance formula and Pythagorean theorem to solve for unknown distances.
This document introduces basic geometry concepts such as points, lines, planes, and their intersections. It defines a point as having no size or shape, a line as an infinite set of collinear points, and a plane as a flat surface extending indefinitely. Examples demonstrate identifying geometric shapes from real-world objects and graphing points and lines on a coordinate plane. The summary defines key terms and provides examples of geometric concepts and relationships.
The document discusses inverse functions and relations. It defines an inverse relation as one where the coordinates of a relation are switched, and an inverse function as one where the domain and range of a function are switched. It provides examples of finding the inverse of specific relations and functions by switching their coordinates or domain and range. It also discusses how to determine if two functions are inverses using their graphs and the horizontal line test.
The document discusses composition of functions. It defines composition of functions as using the output of one function as the input of another. It provides an example of composing two functions f and g, showing the steps of evaluating f(g(x)) and g(f(x)) at different values of x. Another example is given with two functions defined by sets of ordered pairs, finding the compositions f∘g and g∘f by evaluating them at different inputs and stating their domains and ranges.
The document discusses operations that can be performed on functions, including addition, subtraction, multiplication, and division. Definitions of each operation are provided, along with examples of applying the operations to specific functions. Addition of functions involves adding the outputs of each function, subtraction involves subtracting the outputs, multiplication involves multiplying the outputs, and division involves dividing the outputs given the denominator function is not equal to 0. Several examples are worked through applying the different operations to functions like f(x)=2x and g(x)=-x+5. The examples also demonstrate evaluating composite functions and restricting domains as needed.
The document discusses determining the number and type of roots of polynomial equations. It states that every polynomial with degree greater than zero has at least one root in the set of complex numbers according to the Fundamental Theorem of Algebra. Descartes' Rule of Signs is introduced, which relates the number of changes in sign of a polynomial's terms to its possible positive and negative real roots. An example problem is worked through applying these concepts to determine the possible number of positive, negative, and imaginary roots.
This document discusses synthetic division and the remainder and factor theorems. It provides examples of using synthetic division to evaluate functions, determine the number of terms in a sequence, and factor polynomials. The key steps of synthetic division are shown, along with checking the remainder and determining common factors. Three examples are worked through to demonstrate these concepts.
This document discusses solving polynomial equations by factoring polynomials. It begins with essential questions and vocabulary about factoring polynomials and solving polynomial equations by factoring. It then provides the number of terms in a polynomial and the corresponding factoring technique that can be used. Examples of factoring various polynomials are also provided. The document aims to teach students how to factor polynomials and solve polynomial equations by factoring.
The document defines key terms and theorems related to trapezoids and kites. It provides definitions for trapezoid, bases, legs of a trapezoid, base angles, isosceles trapezoid, midsegment of a trapezoid, and kite. It also lists theorems about properties of isosceles trapezoids and kites. Two examples problems are included, one finding measures of an isosceles trapezoid and another showing a quadrilateral is a trapezoid.
The document discusses rhombi and squares. It defines a rhombus as a parallelogram with four congruent sides and gives its properties. A square is defined as a parallelogram with four right angles and four congruent sides. The document provides theorems for identifying rhombi and squares. It then gives examples of using the properties and theorems to determine if a shape is a rhombus, rectangle, or square.
The document discusses properties of rectangles. A rectangle is defined as a parallelogram with four right angles. The key properties are that opposite sides are parallel and congruent, opposite angles are congruent, and consecutive angles are supplementary. The diagonals of a rectangle bisect each other and are congruent. Theorems are presented regarding the diagonals of rectangles. Examples apply the properties of rectangles to find missing side lengths, angles, and diagonals. One example uses the distance formula and slope to determine if a quadrilateral is a rectangle.
The document discusses properties of parallelograms and provides examples of determining if a quadrilateral is a parallelogram. It defines four theorems for identifying parallelograms based on opposite sides, opposite angles, bisecting diagonals, and parallel/congruent sides. Examples solve systems of equations to find values of variables such that the quadrilaterals satisfy parallelogram properties. One example uses slopes of side segments to show a quadrilateral is a parallelogram due to parallel opposite sides.
The document discusses properties of parallelograms. It defines a parallelogram as a quadrilateral with two pairs of parallel sides. It then lists several properties of parallelograms: opposite sides are congruent, opposite angles are congruent, consecutive angles are supplementary, and if one angle is a right angle all angles are right angles. It also discusses properties of diagonals in parallelograms, including that diagonals bisect each other and divide the parallelogram into two congruent triangles. Several examples demonstrate using these properties to solve problems about parallelograms.
The document summarizes key concepts about polygons, including:
- The sum of the interior angles of a polygon with n sides is (n-2)180 degrees.
- The sum of the exterior angles of a polygon is 360 degrees.
- Examples are provided to demonstrate calculating sums of interior/exterior angles and finding missing angle measures using angle sums.
- Regular polygons are defined by their number of sides.
The document discusses analyzing graphs of polynomial functions. It provides examples of locating real zeros of polynomials using the location principle and estimating relative maxima and minima. Example 1 analyzes the polynomial f(x) = x^4 - x^3 - 4x^2 + 1 and locates its real zeros between consecutive integer values. Example 2 graphs the polynomial f(x) = x^3 - 3x^2 + 5 and estimates the x-coordinates of relative maxima and minima.
This document discusses polynomial functions. It defines key terms like polynomial in one variable, leading coefficient, and polynomial function. It provides examples of power functions of varying degrees like quadratic, cubic, quartic and quintic functions. The document also includes examples of evaluating polynomial functions, finding degrees and leading coefficients, graphing polynomial functions from tables of values, and describing properties of graphs.
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
How to Manage Your Lost Opportunities in Odoo 17 CRMCeline George
Odoo 17 CRM allows us to track why we lose sales opportunities with "Lost Reasons." This helps analyze our sales process and identify areas for improvement. Here's how to configure lost reasons in Odoo 17 CRM
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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Training: ISO/IEC 27001 Information Security Management System - EN | PECB
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1. SECTION 6-7
The Quadratic Formula
Friday, February 6, 2009
2. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
Friday, February 6, 2009
3. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
−3 = a + b + c
4 = 4a + 2b + c
17 = 9a + 3b + c
Friday, February 6, 2009
4. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
−3 = a + b + c 17 = 9a + 3b + c
4 = 4a + 2b + c
17 = 9a + 3b + c
Friday, February 6, 2009
5. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
−3 = a + b + c 17 = 9a + 3b + c
-4 = -4a - 2b - c
4 = 4a + 2b + c
17 = 9a + 3b + c
Friday, February 6, 2009
6. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
−3 = a + b + c 17 = 9a + 3b + c
-4 = -4a - 2b - c
4 = 4a + 2b + c
17 = 9a + 3b + c
Friday, February 6, 2009
7. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
−3 = a + b + c 17 = 9a + 3b + c
-4 = -4a - 2b - c
4 = 4a + 2b + c
13 = 5a + b
17 = 9a + 3b + c
Friday, February 6, 2009
8. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
−3 = a + b + c 17 = 9a + 3b + c 4 = 4a + 2b + c
-4 = -4a - 2b - c
4 = 4a + 2b + c
13 = 5a + b
17 = 9a + 3b + c
Friday, February 6, 2009
9. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
−3 = a + b + c 17 = 9a + 3b + c 4 = 4a + 2b + c
-4 = -4a - 2b - c 3 = -a - b - c
4 = 4a + 2b + c
13 = 5a + b
17 = 9a + 3b + c
Friday, February 6, 2009
10. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
−3 = a + b + c 17 = 9a + 3b + c 4 = 4a + 2b + c
-4 = -4a - 2b - c 3 = -a - b - c
4 = 4a + 2b + c
13 = 5a + b
17 = 9a + 3b + c
Friday, February 6, 2009
11. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
−3 = a + b + c 17 = 9a + 3b + c 4 = 4a + 2b + c
-4 = -4a - 2b - c 3 = -a - b - c
4 = 4a + 2b + c
13 = 5a + b 7 = 3a + b
17 = 9a + 3b + c
Friday, February 6, 2009
12. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
−3 = a + b + c 17 = 9a + 3b + c 4 = 4a + 2b + c
-4 = -4a - 2b - c 3 = -a - b - c
4 = 4a + 2b + c
13 = 5a + b 7 = 3a + b
17 = 9a + 3b + c
13 = 5a + b
Friday, February 6, 2009
13. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
−3 = a + b + c 17 = 9a + 3b + c 4 = 4a + 2b + c
-4 = -4a - 2b - c 3 = -a - b - c
4 = 4a + 2b + c
13 = 5a + b 7 = 3a + b
17 = 9a + 3b + c
13 = 5a + b
-7 = -3a - b
Friday, February 6, 2009
14. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
−3 = a + b + c 17 = 9a + 3b + c 4 = 4a + 2b + c
-4 = -4a - 2b - c 3 = -a - b - c
4 = 4a + 2b + c
13 = 5a + b 7 = 3a + b
17 = 9a + 3b + c
13 = 5a + b
-7 = -3a - b
Friday, February 6, 2009
15. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
−3 = a + b + c 17 = 9a + 3b + c 4 = 4a + 2b + c
-4 = -4a - 2b - c 3 = -a - b - c
4 = 4a + 2b + c
13 = 5a + b 7 = 3a + b
17 = 9a + 3b + c
13 = 5a + b
-7 = -3a - b
6 = 2a
Friday, February 6, 2009
16. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
−3 = a + b + c 17 = 9a + 3b + c 4 = 4a + 2b + c
-4 = -4a - 2b - c 3 = -a - b - c
4 = 4a + 2b + c
13 = 5a + b 7 = 3a + b
17 = 9a + 3b + c
13 = 5a + b
-7 = -3a - b
6 = 2a
a=3
Friday, February 6, 2009
17. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
−3 = a + b + c 17 = 9a + 3b + c 4 = 4a + 2b + c
-4 = -4a - 2b - c 3 = -a - b - c
4 = 4a + 2b + c
13 = 5a + b 7 = 3a + b
17 = 9a + 3b + c
13 = 5a + b 13 = 5(3) + b
-7 = -3a - b
6 = 2a
a=3
Friday, February 6, 2009
18. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
−3 = a + b + c 17 = 9a + 3b + c 4 = 4a + 2b + c
-4 = -4a - 2b - c 3 = -a - b - c
4 = 4a + 2b + c
13 = 5a + b 7 = 3a + b
17 = 9a + 3b + c
13 = 5a + b 13 = 5(3) + b
-7 = -3a - b 13 = 15 + b
6 = 2a
a=3
Friday, February 6, 2009
19. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
−3 = a + b + c 17 = 9a + 3b + c 4 = 4a + 2b + c
-4 = -4a - 2b - c 3 = -a - b - c
4 = 4a + 2b + c
13 = 5a + b 7 = 3a + b
17 = 9a + 3b + c
13 = 5a + b 13 = 5(3) + b
-7 = -3a - b 13 = 15 + b
6 = 2a b = -2
a=3
Friday, February 6, 2009
20. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
−3 = a + b + c 17 = 9a + 3b + c 4 = 4a + 2b + c
-4 = -4a - 2b - c 3 = -a - b - c
4 = 4a + 2b + c
13 = 5a + b 7 = 3a + b
17 = 9a + 3b + c
13 = 5a + b 13 = 5(3) + b -3 = 3 - 2 + c
-7 = -3a - b 13 = 15 + b
6 = 2a b = -2
a=3
Friday, February 6, 2009
21. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
−3 = a + b + c 17 = 9a + 3b + c 4 = 4a + 2b + c
-4 = -4a - 2b - c 3 = -a - b - c
4 = 4a + 2b + c
13 = 5a + b 7 = 3a + b
17 = 9a + 3b + c
13 = 5a + b 13 = 5(3) + b -3 = 3 - 2 + c
-7 = -3a - b 13 = 15 + b -3 = 1 + c
6 = 2a b = -2
a=3
Friday, February 6, 2009
22. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
−3 = a + b + c 17 = 9a + 3b + c 4 = 4a + 2b + c
-4 = -4a - 2b - c 3 = -a - b - c
4 = 4a + 2b + c
13 = 5a + b 7 = 3a + b
17 = 9a + 3b + c
13 = 5a + b 13 = 5(3) + b -3 = 3 - 2 + c
-7 = -3a - b 13 = 15 + b -3 = 1 + c
6 = 2a b = -2 c = -4
a=3
Friday, February 6, 2009
23. Warm-Up
1. Fit a quadratic model to the following data.
1 2 3 4 5 6
x
-3 4 17 36 61 92
y
−3 = a + b + c 17 = 9a + 3b + c 4 = 4a + 2b + c
-4 = -4a - 2b - c 3 = -a - b - c
4 = 4a + 2b + c
13 = 5a + b 7 = 3a + b
17 = 9a + 3b + c
13 = 5a + b 13 = 5(3) + b -3 = 3 - 2 + c
-7 = -3a - b 13 = 15 + b -3 = 1 + c y = 3x2 - 2x - 4
6 = 2a b = -2 c = -4
a=3
Friday, February 6, 2009
24. Warm-Up
2. Find the y-intercept of your model. Then find the x-intercept, if you can.
y = 3x2 - 2x - 4
Friday, February 6, 2009
25. Warm-Up
2. Find the y-intercept of your model. Then find the x-intercept, if you can.
y = 3x2 - 2x - 4
y-intercept: When x = 0
Friday, February 6, 2009
26. Warm-Up
2. Find the y-intercept of your model. Then find the x-intercept, if you can.
y = 3x2 - 2x - 4
y-intercept: When x = 0
y = 3(0)2 - 2(0) - 4
Friday, February 6, 2009
27. Warm-Up
2. Find the y-intercept of your model. Then find the x-intercept, if you can.
y = 3x2 - 2x - 4
y-intercept: When x = 0
y = 3(0)2 - 2(0) - 4
y=0-0-4
Friday, February 6, 2009
28. Warm-Up
2. Find the y-intercept of your model. Then find the x-intercept, if you can.
y = 3x2 - 2x - 4
y-intercept: When x = 0
y = 3(0)2 - 2(0) - 4
y=0-0-4
y = -4
Friday, February 6, 2009
29. Warm-Up
2. Find the y-intercept of your model. Then find the x-intercept, if you can.
y = 3x2 - 2x - 4
y-intercept: When x = 0
y = 3(0)2 - 2(0) - 4
y=0-0-4
y = -4
y-intercept: (0, -4)
Friday, February 6, 2009
30. Warm-Up
2. Find the y-intercept of your model. Then find the x-intercept, if you can.
y = 3x2 - 2x - 4
y-intercept: When x = 0 x-intercept: When y = 0
y = 3(0)2 - 2(0) - 4
y=0-0-4
y = -4
y-intercept: (0, -4)
Friday, February 6, 2009
31. Warm-Up
2. Find the y-intercept of your model. Then find the x-intercept, if you can.
y = 3x2 - 2x - 4
y-intercept: When x = 0 x-intercept: When y = 0
y = 3(0)2 - 2(0) - 4 0 = 3x2 - 2x - 4
y=0-0-4
y = -4
y-intercept: (0, -4)
Friday, February 6, 2009
32. Warm-Up
2. Find the y-intercept of your model. Then find the x-intercept, if you can.
y = 3x2 - 2x - 4
y-intercept: When x = 0 x-intercept: When y = 0
y = 3(0)2 - 2(0) - 4 0 = 3x2 - 2x - 4
y=0-0-4 4 = 3x2 - 2x
y = -4
y-intercept: (0, -4)
Friday, February 6, 2009
33. Warm-Up
2. Find the y-intercept of your model. Then find the x-intercept, if you can.
y = 3x2 - 2x - 4
y-intercept: When x = 0 x-intercept: When y = 0
y = 3(0)2 - 2(0) - 4 0 = 3x2 - 2x - 4
y=0-0-4 4 = 3x2 - 2x
y = -4 How do we solve for x?
y-intercept: (0, -4)
Friday, February 6, 2009
34. Warm-Up
2. Find the y-intercept of your model. Then find the x-intercept, if you can.
y = 3x2 - 2x - 4
y-intercept: When x = 0 x-intercept: When y = 0
y = 3(0)2 - 2(0) - 4 0 = 3x2 - 2x - 4
y=0-0-4 4 = 3x2 - 2x
y = -4 How do we solve for x?
y-intercept: (0, -4) Complete the square!
Friday, February 6, 2009
51. Example 2
Pop Fligh’s problem (p. 382 in the book): When is the ball 50 feet high?
Friday, February 6, 2009
52. Example 2
Pop Fligh’s problem (p. 382 in the book): When is the ball 50 feet high?
50 = -.005x2 + 2x + 3.5
Friday, February 6, 2009
53. Example 2
Pop Fligh’s problem (p. 382 in the book): When is the ball 50 feet high?
50 = -.005x2 + 2x + 3.5
0 = -.005x2 + 2x - 46.5
Friday, February 6, 2009
54. Example 2
Pop Fligh’s problem (p. 382 in the book): When is the ball 50 feet high?
50 = -.005x2 + 2x + 3.5
0 = -.005x2 + 2x - 46.5
2
−b ± b − 4ac
x=
2a
Friday, February 6, 2009
55. Example 2
Pop Fligh’s problem (p. 382 in the book): When is the ball 50 feet high?
50 = -.005x2 + 2x + 3.5
0 = -.005x2 + 2x - 46.5
2
−b ± b − 4ac −2 ± 2 − 4(−.005)(−46.5)
2
x= =
2(−.005)
2a
Friday, February 6, 2009
56. Example 2
Pop Fligh’s problem (p. 382 in the book): When is the ball 50 feet high?
50 = -.005x2 + 2x + 3.5
0 = -.005x2 + 2x - 46.5
2
−2 ± 4 − .93
−b ± b − 4ac −2 ± 2 − 4(−.005)(−46.5)
2
x= = =
2(−.005)
2a −.01
Friday, February 6, 2009
57. Example 2
Pop Fligh’s problem (p. 382 in the book): When is the ball 50 feet high?
50 = -.005x2 + 2x + 3.5
0 = -.005x2 + 2x - 46.5
2
−2 ± 4 − .93
−b ± b − 4ac −2 ± 2 − 4(−.005)(−46.5)
2
x= = =
2(−.005)
2a −.01
−2 ± 3.07
=
−.01
Friday, February 6, 2009
58. Example 2
Pop Fligh’s problem (p. 382 in the book): When is the ball 50 feet high?
50 = -.005x2 + 2x + 3.5
0 = -.005x2 + 2x - 46.5
2
−2 ± 4 − .93
−b ± b − 4ac −2 ± 2 − 4(−.005)(−46.5)
2
x= = =
2(−.005)
2a −.01
−2 ± 3.07
=
−.01
Friday, February 6, 2009
59. Example 2
Pop Fligh’s problem (p. 382 in the book): When is the ball 50 feet high?
50 = -.005x2 + 2x + 3.5
0 = -.005x2 + 2x - 46.5
2
−2 ± 4 − .93
−b ± b − 4ac −2 ± 2 − 4(−.005)(−46.5)
2
x= = =
2(−.005)
2a −.01
−2 + 3.07
=
−2 ± 3.07 −.01
=
−.01
Friday, February 6, 2009
60. Example 2
Pop Fligh’s problem (p. 382 in the book): When is the ball 50 feet high?
50 = -.005x2 + 2x + 3.5
0 = -.005x2 + 2x - 46.5
2
−2 ± 4 − .93
−b ± b − 4ac −2 ± 2 − 4(−.005)(−46.5)
2
x= = =
2(−.005)
2a −.01
−2 + 3.07
=
−2 ± 3.07 −.01
=
−2 − 3.07
−.01
=
−.01
Friday, February 6, 2009
61. Example 2
Pop Fligh’s problem (p. 382 in the book): When is the ball 50 feet high?
50 = -.005x2 + 2x + 3.5
0 = -.005x2 + 2x - 46.5
2
−2 ± 4 − .93
−b ± b − 4ac −2 ± 2 − 4(−.005)(−46.5)
2
x= = =
2(−.005)
2a −.01
−2 + 3.07
≈ 24.79
=
−2 ± 3.07 −.01
=
−2 − 3.07
−.01
=
−.01
Friday, February 6, 2009
62. Example 2
Pop Fligh’s problem (p. 382 in the book): When is the ball 50 feet high?
50 = -.005x2 + 2x + 3.5
0 = -.005x2 + 2x - 46.5
2
−2 ± 4 − .93
−b ± b − 4ac −2 ± 2 − 4(−.005)(−46.5)
2
x= = =
2(−.005)
2a −.01
−2 + 3.07
≈ 24.79
=
−2 ± 3.07 −.01
=
−2 − 3.07
−.01
≈ 375.21
=
−.01
Friday, February 6, 2009
63. Example 2
Pop Fligh’s problem (p. 382 in the book): When is the ball 50 feet high?
50 = -.005x2 + 2x + 3.5
0 = -.005x2 + 2x - 46.5
2
−2 ± 4 − .93
−b ± b − 4ac −2 ± 2 − 4(−.005)(−46.5)
2
x= = =
2(−.005)
2a −.01
−2 + 3.07
≈ 24.79
=
−2 ± 3.07 −.01
=
−2 − 3.07
−.01
≈ 375.21
=
−.01
The ball is about either 24.79 feet or 375.21 feet away.
Friday, February 6, 2009
64. So we need our standard form to use the quadratic
formula. Why is that?
Friday, February 6, 2009
66. Homework
p. 385 #1-26
“It was a high counsel that I once heard given to a young person, ‘Always do
what you are afraid to do.’” - Ralph Waldo Emerson
Friday, February 6, 2009