The document discusses the concept of slope and the difference quotient formula for calculating slope. It defines a function f(x) and points P(x,f(x)) and Q(x+h, f(x+h)) on the graph of f(x). The slope of the cord connecting points P and Q is given by the difference quotient (f(x+h) - f(x))/h. An example problem calculates this slope for the specific points P(2,2) and Q(2.2,2.44) on the parabola y=x^2 - 2x + 2.
The document discusses exponential and logarithmic functions. Exponential functions of the form f(x) = b^x are called exponential functions in base b. Logarithmic functions log_b(y) represent the exponent x needed to raise the base b to a power to get the output y. The exponential form b^x = y and logarithmic form x = log_b(y) describe the same relationship between the base b, exponent x, and output y. Questions can be translated between these forms by rewriting the exponential expression as a logarithm or vice versa. Examples demonstrate rewriting expressions and graphing logarithmic functions.
There are two systems for measuring angles: the degree system and the radian system. The degree system divides a full circle into 360 equal angles of 1 degree each. The radian system defines an angle as the arc length cut out by the angle on a unit circle of radius 1, where a full circle corresponds to 2π radians. While the degree system is commonly used, the radian system is preferred in mathematics due to its relationship to circle geometry formulas involving arc lengths and wedge areas.
- The derivative of a function f(x) represents the instantaneous rate of change of the output y with respect to the input x. It is equivalent to the slope of the tangent line and the amount of change in y for a 1 unit change in x.
- For a linear price-demand function of y = f(x) chickens sold given price x, the derivative of the revenue function R(x) = x*f(x) represents how revenue changes with a 1 unit change in price.
- The price that maximizes revenue occurs when the derivative of the revenue function R'(x) is 0, as this is where revenue is no longer increasing or decreasing with small changes in price.
This document discusses rules for computing derivatives of functions. It begins by listing existing derivative rules and defining notation. It then derives and presents rules for the derivatives of trigonometric functions like sine, cosine, tangent, cotangent, secant and cosecant. An example problem demonstrates finding the derivative of the tangent function using previous rules.
The document discusses limits of fractional expressions as the variable approaches certain values. It provides four basic facts about the limits of fractions of elementary functions: (1) if the numerator and denominator have defined limits, the fractional limit is the fraction of the limits; (2) if the numerator is bounded and the denominator diverges, the fractional limit is 0; (3) if the numerator diverges and the denominator is bounded, the fractional limit is infinity; (4) if both the numerator and denominator have limits of 0 or infinity, the fractional limit is inconclusive. It emphasizes that an undefined fractional limit does not necessarily mean the limit is inconclusive - it may simply not exist. Rationalizing expressions can sometimes resolve inconclusive fractional limits
The document discusses related rates problems. It begins by using resizing a rectangle on a computer screen as an example to demonstrate how the rates of change of the length (L) and width (W) relate to the rate of change of the area (A). The key steps are: (1) the area A is given by A=LW, (2) take the derivative of both sides, (3) use the product rule and chain rule to obtain A'=L'W+LW', (4) plug in the given rates of L' and W' to solve for A'.
The document then provides examples to demonstrate how to set up and solve related rates problems by translating the given rates into derivatives, applying
1) The document discusses derivatives as rates of change, using the example of a stone thrown straight up.
2) It is found that the stone will stay in the air for 6 seconds, reaching its maximum height of 144 feet after 3 seconds.
3) The derivative of the height function D(t) represents the instantaneous rate of change of height, or speed, at each time t. This rate varies throughout the stone's trajectory.
The document discusses evaluating the formula log[(2x+1)/(sin1/3(x)+1)] at x=0 and x=10 degrees using a scientific calculator. It explains that the answer is 0 at x=0 and approximately 1.13 at x=10 degrees. It then describes the keyboard of a typical scientific calculator, noting the number, operation, yx, sin, log and formula keys. The rest of the document provides examples and definitions of algebraic, trigonometric and exponential-log formulas.
The document discusses exponential and logarithmic functions. Exponential functions of the form f(x) = b^x are called exponential functions in base b. Logarithmic functions log_b(y) represent the exponent x needed to raise the base b to a power to get the output y. The exponential form b^x = y and logarithmic form x = log_b(y) describe the same relationship between the base b, exponent x, and output y. Questions can be translated between these forms by rewriting the exponential expression as a logarithm or vice versa. Examples demonstrate rewriting expressions and graphing logarithmic functions.
There are two systems for measuring angles: the degree system and the radian system. The degree system divides a full circle into 360 equal angles of 1 degree each. The radian system defines an angle as the arc length cut out by the angle on a unit circle of radius 1, where a full circle corresponds to 2π radians. While the degree system is commonly used, the radian system is preferred in mathematics due to its relationship to circle geometry formulas involving arc lengths and wedge areas.
- The derivative of a function f(x) represents the instantaneous rate of change of the output y with respect to the input x. It is equivalent to the slope of the tangent line and the amount of change in y for a 1 unit change in x.
- For a linear price-demand function of y = f(x) chickens sold given price x, the derivative of the revenue function R(x) = x*f(x) represents how revenue changes with a 1 unit change in price.
- The price that maximizes revenue occurs when the derivative of the revenue function R'(x) is 0, as this is where revenue is no longer increasing or decreasing with small changes in price.
This document discusses rules for computing derivatives of functions. It begins by listing existing derivative rules and defining notation. It then derives and presents rules for the derivatives of trigonometric functions like sine, cosine, tangent, cotangent, secant and cosecant. An example problem demonstrates finding the derivative of the tangent function using previous rules.
The document discusses limits of fractional expressions as the variable approaches certain values. It provides four basic facts about the limits of fractions of elementary functions: (1) if the numerator and denominator have defined limits, the fractional limit is the fraction of the limits; (2) if the numerator is bounded and the denominator diverges, the fractional limit is 0; (3) if the numerator diverges and the denominator is bounded, the fractional limit is infinity; (4) if both the numerator and denominator have limits of 0 or infinity, the fractional limit is inconclusive. It emphasizes that an undefined fractional limit does not necessarily mean the limit is inconclusive - it may simply not exist. Rationalizing expressions can sometimes resolve inconclusive fractional limits
The document discusses related rates problems. It begins by using resizing a rectangle on a computer screen as an example to demonstrate how the rates of change of the length (L) and width (W) relate to the rate of change of the area (A). The key steps are: (1) the area A is given by A=LW, (2) take the derivative of both sides, (3) use the product rule and chain rule to obtain A'=L'W+LW', (4) plug in the given rates of L' and W' to solve for A'.
The document then provides examples to demonstrate how to set up and solve related rates problems by translating the given rates into derivatives, applying
1) The document discusses derivatives as rates of change, using the example of a stone thrown straight up.
2) It is found that the stone will stay in the air for 6 seconds, reaching its maximum height of 144 feet after 3 seconds.
3) The derivative of the height function D(t) represents the instantaneous rate of change of height, or speed, at each time t. This rate varies throughout the stone's trajectory.
The document discusses evaluating the formula log[(2x+1)/(sin1/3(x)+1)] at x=0 and x=10 degrees using a scientific calculator. It explains that the answer is 0 at x=0 and approximately 1.13 at x=10 degrees. It then describes the keyboard of a typical scientific calculator, noting the number, operation, yx, sin, log and formula keys. The rest of the document provides examples and definitions of algebraic, trigonometric and exponential-log formulas.
1.2 review on algebra 2-sign charts and inequalitiesmath265
The document discusses sign charts and inequalities. It explains that sign charts can be used to determine if expressions are positive or negative by factoring them and evaluating at given values of x. Examples are provided to demonstrate how to construct a sign chart by: 1) solving for where the expression equals 0, 2) marking these values on a number line, and 3) evaluating the expression at sample points in each segment to determine the signs in between values where the expression equals 0. The sign chart then indicates the ranges where the expression is positive, negative or zero.
This document discusses algebraic expressions and polynomial expressions. It provides examples of algebraic expressions and defines them as formulas constructed with variables and numbers using basic arithmetic operations. Polynomials are defined as expressions of the form anxn + an-1xn-1 + ... + a1x + a0, where the ai's are numbers. The document gives examples of factoring polynomials and evaluating polynomial expressions at given values. It also discusses using factoring to find the roots of polynomial equations.
The document discusses properties of derivatives and how they relate to limits. It states that the sum, difference, and constant multiple rules for limits directly apply to differentiation. However, the product and quotient rules for limits do not directly apply to differentiation, which has more complicated product and quotient rules. Elementary functions are defined in terms of a few basic formulas and operations. The document then examines the sum and constant multiple rules for derivatives in more detail, proving them using limits. It also provides a geometric illustration of how the derivative of a sum is equal to the sum of the derivatives.
3.2 implicit equations and implicit differentiationmath265
The document discusses implicit equations and implicit differentiation. It begins by explaining the difference between explicit and implicit forms of equations, using the example of y=1/x which can be written explicitly as y=1/x or implicitly as xy=1. It then introduces the concept of implicit differentiation, which involves taking the derivative of an implicit equation with respect to x and solving for the derivative of y with respect to x (y’). This allows one to find the slope of the curve at a point, even if the explicit form of the relation between x and y is difficult to determine from the implicit equation.
4.5 continuous functions and differentiable functionsmath265
The document discusses continuous and differentiable functions. It defines elementary functions as those constructed using basic operations like addition and multiplication. Continuous functions over a closed interval are bounded and have absolute maximum and minimum values. The Intermediate Value Theorem states that a continuous function takes on all values between its minimum and maximum. Differentiable functions are continuous. Rolle's Theorem says that if a differentiable function is equal at the endpoints of an interval, its derivative is zero somewhere in between.
This document discusses optimization problems in real-world applications and the role of derivatives. It provides examples of functions that may or may not have extrema over an interval. The extrema theorem for continuous functions states that a continuous function over a closed interval will have both an absolute maximum and minimum. Extrema can occur where the derivative is zero, where the derivative is undefined, or at the endpoints. Examples are provided to illustrate the different types of extrema.
3.3 graphs of factorable polynomials and rational functionsmath265
The document discusses graphs of factorable polynomials. It begins by showing examples of graphs of even and odd degree polynomials like y=x2, y=x4, y=x3, and y=-x5. It then explains that the graphs of polynomials are smooth, unbroken curves. For large values of x, the leading term of a polynomial dominates and determines the graph's behavior. Based on the leading term and whether the degree is even or odd, the graph exhibits one of four behaviors as x approaches infinity. The document demonstrates how to construct the sign chart of a polynomial from its roots and use it to sketch the central portion of the graph. It provides an example of sketching the graph of y=x
The document summarizes different types of derivatives. It discusses simple derivatives where there is one input and output, and defines them. It then discusses implicit derivatives where a relationship between two variables is given and the derivative of one with respect to the other is sought using implicit differentiation. An example finds the derivative of u with respect to v and v with respect to u for the equation 2u^2 - v^3 = 2 - uv. Reciprocal relationships between the derivatives are noted.
The document discusses using sign charts to solve polynomial and rational inequalities. It provides examples of solving inequalities by setting one side equal to zero, factoring the expression, drawing the sign chart, and determining the solutions from the regions with the appropriate signs. Specifically, it works through examples of solving x^2 - 3x > 4, 2x^2 - x^3/(x^2 - 2x + 1) < 0, and (x - 2)/(2/(x - 1)) < 3.
5.3 areas, riemann sums, and the fundamental theorem of calaculusmath265
The document defines definite integrals and Riemann sums. It states that a definite integral calculates the area under a function between limits a and b by dividing the interval into subintervals and summing the areas of rectangles approximating the function over each subinterval. Riemann sums make this approximation explicit by taking the width of each subinterval times the value of the function at a sample point in the subinterval. In the limit as the subintervals approach zero width, the Riemann sum converges to the true integral value.
This document discusses first degree functions and linear equations. It explains that most real-world mathematical functions can be composed of algebraic, trigonometric, or exponential/log formulas. Linear equations of the form Ax + By = C represent straight lines that can be graphed by finding the x- and y-intercepts. If an equation contains only one variable, it represents a vertical or horizontal line. The slope-intercept form y = mx + b is introduced, where m is the slope and b is the y-intercept. Slope is defined as the ratio of the rise over the run between two points on a line.
The document discusses calculating the volumes of solids of revolution using Cavalieri's principle and the fundamental theorem of calculus. It provides an example of finding the volume of a solid generated by revolving a semi-circular base of radius r around its diameter, which is calculated to be 2r^3/3. The document also describes approximating a solid of revolution as cylindrical shells and calculating volume as 2πrhΔx.
The document discusses the substitution method of integration. It explains that while the derivative of an elementary function is another elementary function, the antiderivative may not be. There are two main integration methods: substitution and integration by parts. Substitution reverses the chain rule by letting u be a function of x with derivative u', then substituting u for x and replacing dx with du/u' in the integral.
The document discusses slopes and derivatives. It defines slope as the ratio of the "rise" over the "run" between two points on a line. For a curve, the slope at a point is defined as the slope of the tangent line at that point. The derivative at a point is also called the slope of the tangent line and represents the instantaneous rate of change of the function at that point. The document provides an example of using slopes to calculate rates like velocity and fuel efficiency from distance and time measurements.
The document discusses using the second derivative to identify extrema and classify flat points on a graph of y=f(x). It defines terms for the second derivative, explaining that if f''(x)>0, the slope f'(x) is increasing, meaning a downhill point is getting less steep and an uphill point is getting more steep. For a maximum point M, the curve must flatten out with f'(x) approaching 0+ and f'(x) becoming increasingly negative after M, resulting in f''(M)<0.
The document defines the derivative of a function f(x) as the limit of the difference quotient (f(x+h) - f(x))/h as h approaches 0. This represents the slope of the tangent line to the function f(x) at the point x. An example is worked out where the derivative of the function f(x) = x^2 - 2x + 2 is calculated to be 2x - 2. The derivative is denoted by f'(x) and represents the instantaneous rate of change of the function at the point x.
The document discusses quadratic functions and parabolas. It defines quadratic functions as functions of the form y = ax2 + bx + c, where a ≠ 0. It states that the graphs of quadratic equations are called parabolas. Parabolas are symmetric around a central line, with the vertex (highest/lowest point) located on this line. The vertex formula is given as x = -b/2a. Steps for graphing a parabola are outlined, including finding the vertex, another point, and reflections across the central line. An example graphs the parabola y = x2 - 4x - 12, finding the vertex as (2, -16) and x-intercepts as -
The document discusses calculating the area of a 2D region R. It explains that the area can be found by taking a ruler and measuring the span of R from x=a to x=b. The cross-sectional length L(x) is defined at each x value. The region is divided into subintervals with arbitrary points xi selected in each. Rectangles with base Δx and height L(xi) approximate the area in each subinterval. The Riemann sum of these rectangles approximates the total area of R. The mathematical definition of the area is given as the definite integral of the cross-section function from a to b, according to the Fundamental Theorem of Calculus. An example problem finds the area
The document discusses factorable polynomials and graphing them. It defines a factorable polynomial P(x) as one that can be written as the product of linear factors P(x) = an(x - r1)(x - r2)...(x - rk), where r1, r2, etc. are the roots of P(x). It explains that for large values of |x|, the leading term of P(x) dominates so the graph resembles that of the leading term, while near the roots other terms contribute to the shape of the graph. Examples of graphs of polynomials like x^n are provided to illustrate the approach.
6.2 special cases system of linear equationsmath260
The document discusses special cases of systems of linear equations, including inconsistent/contradictory systems that have no solution, dependent systems that have infinitely many solutions, and the process of putting a system's augmented matrix into row-reduced echelon form (rref-form) to identify which type it is. It provides examples of an inconsistent system with equations x+y=2 and x+y=3, and a dependent system with equations x+y=2 and 2x+2y=4.
The document discusses limits and derivatives. It explains that in calculating the derivative of f(x)=x^2 - 2x + 2, the slope formula was simplified. As h approaches 0, the chords slide towards the tangent line, so the slope at (x,f(x)) is 2x-2. It then provides definitions and explanations for what it means for a variable to approach 0 from the right, left, or in general, to clarify the procedure of obtaining slopes using limits.
The document discusses various chain rules for derivatives, including:
- The power chain rule: [up]' = pup−1(u)'
- Trigonometric chain rules: [sin(u)]' = cos(u)(u)', [cos(u)]' = −sin(u)(u)'
- Examples are provided to demonstrate applying the chain rules to find derivatives of more complex functions like y = sin(x3) and y = sin3(x). Repeated application of the appropriate chain rule at each step is often required.
1.2 review on algebra 2-sign charts and inequalitiesmath265
The document discusses sign charts and inequalities. It explains that sign charts can be used to determine if expressions are positive or negative by factoring them and evaluating at given values of x. Examples are provided to demonstrate how to construct a sign chart by: 1) solving for where the expression equals 0, 2) marking these values on a number line, and 3) evaluating the expression at sample points in each segment to determine the signs in between values where the expression equals 0. The sign chart then indicates the ranges where the expression is positive, negative or zero.
This document discusses algebraic expressions and polynomial expressions. It provides examples of algebraic expressions and defines them as formulas constructed with variables and numbers using basic arithmetic operations. Polynomials are defined as expressions of the form anxn + an-1xn-1 + ... + a1x + a0, where the ai's are numbers. The document gives examples of factoring polynomials and evaluating polynomial expressions at given values. It also discusses using factoring to find the roots of polynomial equations.
The document discusses properties of derivatives and how they relate to limits. It states that the sum, difference, and constant multiple rules for limits directly apply to differentiation. However, the product and quotient rules for limits do not directly apply to differentiation, which has more complicated product and quotient rules. Elementary functions are defined in terms of a few basic formulas and operations. The document then examines the sum and constant multiple rules for derivatives in more detail, proving them using limits. It also provides a geometric illustration of how the derivative of a sum is equal to the sum of the derivatives.
3.2 implicit equations and implicit differentiationmath265
The document discusses implicit equations and implicit differentiation. It begins by explaining the difference between explicit and implicit forms of equations, using the example of y=1/x which can be written explicitly as y=1/x or implicitly as xy=1. It then introduces the concept of implicit differentiation, which involves taking the derivative of an implicit equation with respect to x and solving for the derivative of y with respect to x (y’). This allows one to find the slope of the curve at a point, even if the explicit form of the relation between x and y is difficult to determine from the implicit equation.
4.5 continuous functions and differentiable functionsmath265
The document discusses continuous and differentiable functions. It defines elementary functions as those constructed using basic operations like addition and multiplication. Continuous functions over a closed interval are bounded and have absolute maximum and minimum values. The Intermediate Value Theorem states that a continuous function takes on all values between its minimum and maximum. Differentiable functions are continuous. Rolle's Theorem says that if a differentiable function is equal at the endpoints of an interval, its derivative is zero somewhere in between.
This document discusses optimization problems in real-world applications and the role of derivatives. It provides examples of functions that may or may not have extrema over an interval. The extrema theorem for continuous functions states that a continuous function over a closed interval will have both an absolute maximum and minimum. Extrema can occur where the derivative is zero, where the derivative is undefined, or at the endpoints. Examples are provided to illustrate the different types of extrema.
3.3 graphs of factorable polynomials and rational functionsmath265
The document discusses graphs of factorable polynomials. It begins by showing examples of graphs of even and odd degree polynomials like y=x2, y=x4, y=x3, and y=-x5. It then explains that the graphs of polynomials are smooth, unbroken curves. For large values of x, the leading term of a polynomial dominates and determines the graph's behavior. Based on the leading term and whether the degree is even or odd, the graph exhibits one of four behaviors as x approaches infinity. The document demonstrates how to construct the sign chart of a polynomial from its roots and use it to sketch the central portion of the graph. It provides an example of sketching the graph of y=x
The document summarizes different types of derivatives. It discusses simple derivatives where there is one input and output, and defines them. It then discusses implicit derivatives where a relationship between two variables is given and the derivative of one with respect to the other is sought using implicit differentiation. An example finds the derivative of u with respect to v and v with respect to u for the equation 2u^2 - v^3 = 2 - uv. Reciprocal relationships between the derivatives are noted.
The document discusses using sign charts to solve polynomial and rational inequalities. It provides examples of solving inequalities by setting one side equal to zero, factoring the expression, drawing the sign chart, and determining the solutions from the regions with the appropriate signs. Specifically, it works through examples of solving x^2 - 3x > 4, 2x^2 - x^3/(x^2 - 2x + 1) < 0, and (x - 2)/(2/(x - 1)) < 3.
5.3 areas, riemann sums, and the fundamental theorem of calaculusmath265
The document defines definite integrals and Riemann sums. It states that a definite integral calculates the area under a function between limits a and b by dividing the interval into subintervals and summing the areas of rectangles approximating the function over each subinterval. Riemann sums make this approximation explicit by taking the width of each subinterval times the value of the function at a sample point in the subinterval. In the limit as the subintervals approach zero width, the Riemann sum converges to the true integral value.
This document discusses first degree functions and linear equations. It explains that most real-world mathematical functions can be composed of algebraic, trigonometric, or exponential/log formulas. Linear equations of the form Ax + By = C represent straight lines that can be graphed by finding the x- and y-intercepts. If an equation contains only one variable, it represents a vertical or horizontal line. The slope-intercept form y = mx + b is introduced, where m is the slope and b is the y-intercept. Slope is defined as the ratio of the rise over the run between two points on a line.
The document discusses calculating the volumes of solids of revolution using Cavalieri's principle and the fundamental theorem of calculus. It provides an example of finding the volume of a solid generated by revolving a semi-circular base of radius r around its diameter, which is calculated to be 2r^3/3. The document also describes approximating a solid of revolution as cylindrical shells and calculating volume as 2πrhΔx.
The document discusses the substitution method of integration. It explains that while the derivative of an elementary function is another elementary function, the antiderivative may not be. There are two main integration methods: substitution and integration by parts. Substitution reverses the chain rule by letting u be a function of x with derivative u', then substituting u for x and replacing dx with du/u' in the integral.
The document discusses slopes and derivatives. It defines slope as the ratio of the "rise" over the "run" between two points on a line. For a curve, the slope at a point is defined as the slope of the tangent line at that point. The derivative at a point is also called the slope of the tangent line and represents the instantaneous rate of change of the function at that point. The document provides an example of using slopes to calculate rates like velocity and fuel efficiency from distance and time measurements.
The document discusses using the second derivative to identify extrema and classify flat points on a graph of y=f(x). It defines terms for the second derivative, explaining that if f''(x)>0, the slope f'(x) is increasing, meaning a downhill point is getting less steep and an uphill point is getting more steep. For a maximum point M, the curve must flatten out with f'(x) approaching 0+ and f'(x) becoming increasingly negative after M, resulting in f''(M)<0.
The document defines the derivative of a function f(x) as the limit of the difference quotient (f(x+h) - f(x))/h as h approaches 0. This represents the slope of the tangent line to the function f(x) at the point x. An example is worked out where the derivative of the function f(x) = x^2 - 2x + 2 is calculated to be 2x - 2. The derivative is denoted by f'(x) and represents the instantaneous rate of change of the function at the point x.
The document discusses quadratic functions and parabolas. It defines quadratic functions as functions of the form y = ax2 + bx + c, where a ≠ 0. It states that the graphs of quadratic equations are called parabolas. Parabolas are symmetric around a central line, with the vertex (highest/lowest point) located on this line. The vertex formula is given as x = -b/2a. Steps for graphing a parabola are outlined, including finding the vertex, another point, and reflections across the central line. An example graphs the parabola y = x2 - 4x - 12, finding the vertex as (2, -16) and x-intercepts as -
The document discusses calculating the area of a 2D region R. It explains that the area can be found by taking a ruler and measuring the span of R from x=a to x=b. The cross-sectional length L(x) is defined at each x value. The region is divided into subintervals with arbitrary points xi selected in each. Rectangles with base Δx and height L(xi) approximate the area in each subinterval. The Riemann sum of these rectangles approximates the total area of R. The mathematical definition of the area is given as the definite integral of the cross-section function from a to b, according to the Fundamental Theorem of Calculus. An example problem finds the area
The document discusses factorable polynomials and graphing them. It defines a factorable polynomial P(x) as one that can be written as the product of linear factors P(x) = an(x - r1)(x - r2)...(x - rk), where r1, r2, etc. are the roots of P(x). It explains that for large values of |x|, the leading term of P(x) dominates so the graph resembles that of the leading term, while near the roots other terms contribute to the shape of the graph. Examples of graphs of polynomials like x^n are provided to illustrate the approach.
6.2 special cases system of linear equationsmath260
The document discusses special cases of systems of linear equations, including inconsistent/contradictory systems that have no solution, dependent systems that have infinitely many solutions, and the process of putting a system's augmented matrix into row-reduced echelon form (rref-form) to identify which type it is. It provides examples of an inconsistent system with equations x+y=2 and x+y=3, and a dependent system with equations x+y=2 and 2x+2y=4.
The document discusses limits and derivatives. It explains that in calculating the derivative of f(x)=x^2 - 2x + 2, the slope formula was simplified. As h approaches 0, the chords slide towards the tangent line, so the slope at (x,f(x)) is 2x-2. It then provides definitions and explanations for what it means for a variable to approach 0 from the right, left, or in general, to clarify the procedure of obtaining slopes using limits.
The document discusses various chain rules for derivatives, including:
- The power chain rule: [up]' = pup−1(u)'
- Trigonometric chain rules: [sin(u)]' = cos(u)(u)', [cos(u)]' = −sin(u)(u)'
- Examples are provided to demonstrate applying the chain rules to find derivatives of more complex functions like y = sin(x3) and y = sin3(x). Repeated application of the appropriate chain rule at each step is often required.
This document discusses exponents and exponent rules. It defines exponents as multiplying a base A by itself repeatedly N times, written as AN. It then provides several exponent rules including:
- Multiply-Add Rule: AnAk = An+k
- Divide-Subtract Rule: An/Ak = An-k
- Power-Multiply Rule: (An)k = Ank
Special exponents are also discussed such as A0=1 if A≠0, A-k=1/Ak, and calculating fractional exponents by extracting the root first then raising it to the numerator power. Examples are provided to demonstrate applying these exponent rules and calculating fractional exponents.
The document discusses continuity of functions and graphs. It defines a continuous function as one where the graph is unbroken within its domain. A function is discontinuous if its graph is broken. Continuity at a point x=a can be determined by comparing the left and right limits of the function at a to the actual value of the function at a. If the limits are equal to the function value, it is continuous from that side. The document provides examples of functions that are right continuous, left continuous, or discontinuous at various points to illustrate these concepts.
This document presents algorithmic puzzles and their solutions. It discusses puzzles involving counterfeit coins, uneven water pitchers, strong eggs on tiny floors, and people arranged in a circle. For each puzzle, it provides the problem description, an analysis or solution approach, and sometimes additional discussion. The document is a presentation on algorithmic puzzles given by Amrinder Arora, including their contact information.
Euclid's Algorithm for Greatest Common Divisor - Time Complexity AnalysisAmrinder Arora
Euclid's algorithm for finding greatest common divisor is an elegant algorithm that can be written iteratively as well as recursively. The time complexity of this algorithm is O(log^2 n) where n is the larger of the two inputs.
Convex Hull - Chan's Algorithm O(n log h) - Presentation by Yitian Huang and ...Amrinder Arora
Chan's Algorithm for Convex Hull Problem. Output Sensitive Algorithm. Takes O(n log h) time. Presentation for the final project in CS 6212/Spring/Arora.
The document discusses properties of logarithms. It begins by recalling rules of exponents and their corresponding rules of logarithms. Four basic logarithm rules are presented: 1) logb(1) = 0, 2) logb(xy) = logb(x) + logb(y), 3) logb(x/y) = logb(x) - logb(y), 4) logb(xt) = tlogb(x). It then works through an example problem to demonstrate using these rules to write the logarithm of a expression in terms of logarithms of its variables. It concludes by noting that logarithms and exponentials are inverse functions, so logb(bx) =
This document discusses dividend policy and the various theories around it. It defines dividends and discusses Walter's model and Gordon's model, which propose that dividend policy affects firm value. It also covers the irrelevance theories of Modigliani-Miller and the traditional approach, which argue that dividend policy does not impact value. The document provides formulas for the different models and discusses their assumptions and criticisms.
The document discusses the concept of slope as it relates to functions. It introduces function notation and defines a function's output f(x). It explains that the slope of the line connecting two points (x, f(x)) and (x+h, f(x+h)) on a function graph is given by the difference quotient formula: m = (f(x+h) - f(x))/h. An example calculates the slope of the cord between points on the graph of f(x) = x^2 - 2x + 2.
The document discusses calculating the slope of a curve between two points (x, f(x)) and (x+h, f(x+h)) using the difference quotient formula. It defines the difference quotient as (f(x+h) - f(x))/h, where h is the difference between x and x+h. An example calculates the slope between the points (2, f(2)) and (2.2, f(2.2)) for the function f(x) = x^2 - 2x + 2, finding the slope to be 0.44.
The document discusses the difference quotient formula for calculating the slope of a cord connecting two points (x, f(x)) and (x+h, f(x+h)) on a function graph. It defines the difference quotient as (f(x+h) - f(x))/h, which calculates the slope as the change in y-values (f(x+h) - f(x)) over the change in x-values (h). An example calculates the slope of the cord connecting the points (2, f(2)) and (2.2, f(2.2)) on the function f(x) = x^2 - 2x + 2.
The document discusses the difference quotient formula for calculating the slope between two points (x1,y1) and (x2,y2) on a function y=f(x). It shows that the slope m is equal to (f(x+h)-f(x))/h, where h is the difference between x1 and x2. This "difference quotient" formula allows slopes to be calculated from the values of a function at two nearby points. Examples are given of simplifying the difference quotient for quadratic and rational functions.
This document introduces vector fields and defines scalar and vector fields. It defines a vector field F over a planar region D as a function that assigns a vector to each point, given by the components P and Q. Similarly, a vector field over a spatial region E is given by components P, Q, and R. Examples of vector fields include velocity fields and gravitational and electric force fields. It also defines the gradient of a scalar field, divergence and curl of a vector field, and discusses integral calculations for scalar and vector fields along curves.
6.6 analyzing graphs of quadratic functionsJessica Garcia
This document discusses analyzing and graphing quadratic functions. It defines key terms like vertex, axis of symmetry, and vertex form. It explains that the graph of y=ax^2 is a parabola, and how the value of a affects whether the parabola opens up or down. It also describes how to graph quadratic functions in vertex form by plotting the vertex and axis of symmetry, and using symmetry.
The document provides an overview of Calculus I taught by Professor Matthew Leingang at New York University. It outlines key topics that will be covered in the course, including different classes of functions, transformations of functions, and compositions of functions. The first assignments are due on January 31 and February 2, with first recitations on February 3. The document uses examples to illustrate concepts like linear functions, other polynomial functions, and trigonometric functions. It also explains how vertical and horizontal shifts can transform the graph of a function.
Lesson 2: A Catalog of Essential Functions (slides)Matthew Leingang
This document provides an overview of different types of functions including: linear, polynomial, rational, power, trigonometric, and exponential functions. It discusses representing functions verbally, numerically, visually, and symbolically. Key topics covered include transformations of functions through shifting graphs vertically and horizontally, as well as composing multiple functions.
The document defines quadratic functions and discusses their various forms, including general, vertex, and factored forms. It also covers solving quadratic equations using methods like the quadratic formula, factoring, and completing the square. Additionally, it discusses key features of quadratic graphs like x-intercepts, y-intercepts, the vertex, and concavity. Examples are provided to illustrate finding these features and graphing parabolas.
1) The document discusses directional derivatives and the gradient of functions of several variables. It defines the directional derivative Duf(c) as the slope of the function f in the direction of the unit vector u at the point c.
2) It shows that the partial derivatives of f can be computed by treating all but one variable as a constant. The gradient of f is defined as the vector of its partial derivatives.
3) It derives an expression for the directional derivative Duf(c) in terms of the partial derivatives of f and the components of the unit vector u, showing the relationship between directional derivatives and the gradient.
The document discusses various transformations that can be performed on graphs of functions, including vertical translations, stretches, and compressions. Vertical translations move the entire graph up or down by adding or subtracting a constant to the function. Stretches elongate or compress the graph vertically by multiplying the function by a constant greater than or less than 1, respectively. These transformations can be represented by modifying the original function in a way that corresponds to the geometric transformation of its graph.
The document discusses various transformations that can be performed on graphs of functions, including vertical translations, stretches and compressions, and vertical reflections. Vertical translations move the graph up or down by adding or subtracting a constant value to the output. Stretches and compressions multiply the output by a constant value greater than or less than 1, respectively. Reflecting the output about the x-axis vertically reflects the entire graph. These transformations can be represented by modifying the original function definition.
Parent functions are families of graphs that share unique properties. Transformations can move the graph around the plane. The main parent functions explored are the constant, linear, absolute value, quadratic, cubic, square root, cubic root, and exponential functions. Each has a characteristic shape and number of intercepts. Domains and ranges depend on the specific function but often extend to positive and negative infinity.
The document discusses graphing quadratic functions. It defines a quadratic function as f(x) = ax^2 + bx + c where a, b, and c are real numbers and a is not equal to 0. The graph of a quadratic function is a parabola that is symmetrical about an axis. When the leading coefficient a is positive, the parabola opens upward and the vertex is a minimum. When a is negative, the parabola opens downward and the vertex is a maximum. Standard forms for quadratic functions and methods for finding characteristics like the vertex, axis of symmetry, and x-intercepts from the equation are also presented.
This document provides information about circles and conic sections. It begins with an overview of circles, including definitions of key terms like radius, diameter, chord, and equations of circles given the center and radius or three points. It then covers conic sections, defining ellipses, parabolas and hyperbolas based on eccentricity. Equations of various conic sections are derived based on the location of foci, directrix, vertex and other geometric properties. Sample problems are provided to demonstrate solving problems involving different geometric configurations of circles and conic sections.
This document outlines the contents of a Mathematics II course, including five units: vector calculus, Fourier series and Fourier transforms, interpolation and curve fitting, solutions to algebraic/transcendental equations and linear systems of equations, and numerical integration and solutions to differential equations. It lists three textbooks and four references used in the course. It then provides examples and explanations of key concepts from the first two units, including vector differential operators, gradient, divergence, curl, and Fourier series representations of functions.
The document discusses transformations of quadratic functions in vertex form f(x) = a(x-h)2 + k. It explains how changing the coefficients a, h, and k affects the graph of the quadratic function. Specifically, it states that changing a widens or narrows the graph, changing h shifts the graph left or right, and changing k shifts the graph up or down. It also provides examples of writing equations for quadratic functions based on given graphs and finding the vertex of a quadratic function in standard form.
This document discusses exponential functions and their graphs. It defines the exponential function f(x) = ax and gives examples. It shows how to evaluate exponential functions at different values of x. It explains the graphs of exponential functions with bases greater than and less than 1, and how they have horizontal asymptotes at y = 0. It provides examples of sketching graphs of exponential functions and stating their domains and ranges. It introduces the irrational number e and the natural exponential function f(x) = ex. It concludes with formulas for compound interest and an example problem.
The document discusses different forms of quadratic equations and how to graph them. It covers the standard form ax^2 + bx + c, vertex form a(x-h)^2 + k, and intercept form a(x-p)(x-q). It explains how to identify the vertex and axis of symmetry in standard form, and how to graph quadratics in all three forms by plotting points and drawing the parabola.
The document discusses parabolas and their key properties. A parabola is defined as the set of points equidistant from a fixed point (the focus) and a fixed line (the directrix). The vertex, axis of symmetry, and focus-directrix distance determine the shape and position of the parabola. Examples are provided to demonstrate how to find the equation of a parabola given properties like the vertex and focus.
Similar to 1.6 slopes and the difference quotient (20)
The document discusses limits and how they are used to calculate the derivative of a function. It defines what it means for a sequence to approach a limit from the right or left side. Graphs and examples are provided to illustrate these concepts. The key rules for calculating limits are outlined, such as using algebra to split limits into their constituent parts. Common types of obvious limits are also stated, such as limits of constants or products involving constants.
The document discusses the concept of limits and clarifies the notation used to describe sequences approaching a number. It explains that saying "x approaches 0 from the right side" means the sequence values only become smaller than 0 after a finite number of terms. Similarly, approaching from the left means only finitely many terms are greater than 0. The direction a sequence approaches a number affects limits like the limit of |x|/x as x approaches 0.
This document discusses two sections, Section 3.1 and Section 3.3, but provides no details about the content or topics covered in either section. The document gives the section numbers and titles but no other informative or descriptive text.
The document describes how to calculate the volume of a solid object using Cavalieri's principle. It involves partitioning the solid into thin cross-sectional slices and approximating the volume of each slice as a cylinder with the slice's cross-sectional area and thickness. The total volume is then approximated as the sum of the cylindrical slice volumes. As the number of slices approaches infinity, this sum approaches the actual volume calculated as the integral of the cross-sectional area function over the solid's distance range.
The document discusses calculating the area of a region R. It introduces using a ruler x to measure the span of R from x=a to x=b. It defines the cross-sectional length L(x) and partitions the interval [a,b] into subintervals. The Riemann sum of the areas of approximating rectangles is shown to approach the actual area of R, defined as the definite integral of L(x) from a to b. As an example, it calculates the area between the curves y=-x^2+2x and y=x^2 by finding the interval spans from 0 to 1 and taking the integral of the difference of the functions.
The document discusses antiderivatives and integration. It defines an antiderivative as a function whose derivative is the original function. The integral of a function is defined as the set of its antiderivatives. Basic integration rules are provided, such as integrating term-by-term and pulling out constants. Formulas for integrating common functions like exponentials, trigonometric functions, and logarithms are listed. An example problem demonstrates finding the antiderivative of a multi-term function by applying the basic integration rules.
The document summarizes different types of derivatives:
Simple derivatives involve a single input and output. Implicit derivatives are taken for equations with two or more variables, treating one as the independent variable. An example finds derivatives of u with respect to v and v with respect to u for the equation 2u^2 - v^3 = 2 - uv. The derivatives are related by the reciprocal relationship in differential notation.
This document contains 20 math word problems involving rates of change of quantities like distance, area, radius, and volume over time. The problems involve concepts like expanding derivatives, rectangles changing size, cars moving at intersections, distances between moving objects, water filling and draining from tanks, ladders on houses, waves expanding in water, balloons deflating, and water filling triangular troughs. Rates of change are calculated for variables like length, width, area, distance, radius, and volume at specific values over time.
The document contains 10 multi-part exercises involving calculating rates of change, finding maximums and optima, and approximating changes in functions. The exercises involve concepts like linear price-demand functions, surface area and volume relationships for geometric objects, and force functions related to physics concepts like gravity and electric force.
1. The document provides instructions for using calculus concepts like derivatives and integrals to approximate values. It contains 14 problems involving finding derivatives, using derivatives to approximate values, finding volumes with integrals, and using Newton's method to find roots of functions.
2. The final problem asks to use Newton's method in Excel to find the two roots of the function y = ex - 2x - 2 that exist between -3 and 3 to 5 decimal places, and then justify that the approximations are correct.
This document contains 16 multi-part math problems involving optimization of functions, geometry, and physics. The problems cover topics like finding extrema of functions, finding points on lines, maximizing areas of geometric shapes given constraints, minimizing materials needed to construct cylinders and fences, and finding positions of maximum or minimum values of physical quantities like force and illumination.
This document discusses two applications of tangent lines: differentials and linear approximation, and finding the tangent line T(b) at a nearby point b. It explains that the tangent line T(x) at point (a, f(a)) is given by T(x) = f'(a)(x - a) + f(a). The slope f'(a) is identified with the derivative dy/dx. There are two ways to find T(b): directly using T(x), or by finding the differential ΔT = dy and using ΔT + f(a) = T(b).
The document discusses how derivatives can represent rates of change. It states that given a function f(x), the derivative f'(a) is equivalent to the slope of the tangent line at x=a, the instantaneous rate of change of y with respect to x at x=a, and the amount of change in y for a 1 unit change in x at x=a. It then provides an example using a price-demand function for chickens, finding that the maximum revenue of $1152 occurs at a price of $10 per chicken.
1. Graph and analyze the critical points, extrema, inflection points, intervals of increasing/decreasing, and intervals of concave up/down for 10 functions.
2. Review homework on finding derivatives using the definition of the difference quotient and evaluating limits. Find the derivatives of 6 functions.
3. Use implicit differentiation to find the derivative of one function defined implicitly and to find points with tangent lines of slope 1 for another implicit function.
4. Find the second derivatives of two functions.
1) The document provides a tutorial on using formulas in Excel, including how to enter formulas, use relative and absolute cell references, perform calculations on ranges of cells, and sum columns of data.
2) It includes steps to enter sample data, calculate values like x-squared and frequencies multiplied by x and x-squared, and use formulas to automatically calculate those values down a column.
3) The tutorial concludes with instructions to sum the sample data columns, enter the student's name, save the Excel file, and provide a printout.
The document discusses derivatives and graphs. It defines interval notation used to indicate whether points are included or excluded from intervals. It then explains that the derivative of a function f(x) at a point x, f'(x), represents the slope of the tangent line to the graph of f(x) at (x, f(x)). Finally, it notes that points where the derivative is 0 are called critical points, as the tangent line is flat at these points.
The document discusses higher order derivatives. It defines the nth derivative of a function f(x) as f(n)(x). The first example finds the first five derivatives of f(x)=2x^4 - x^3 - 2. The second example finds the first three derivatives of f(x)=-x^2/3. The third example finds the first four derivatives of f(x)=ln(x) and discusses how derivatives of rational functions become more complicated with higher orders. It also provides examples of finding derivatives of other functions like sin(x).
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
2. In order to be precise, basic geometric information
and formulas concerning graphs are given in
function notation.
Slopes and the Difference Quotient
3. Given x, the output of a function is denoted as y or
as f(x).
In order to be precise, basic geometric information
and formulas concerning graphs are given in
function notation.
Slopes and the Difference Quotient
4. In order to be precise, basic geometric information
and formulas concerning graphs are given in
function notation.
Slopes and the Difference Quotient
Given x, the output of a function is denoted as y or
as f(x). Hence the coordinate of a generic point
P(x, y) on the graph is often denoted as (x, f(x)).
5. Given x, the output of a function is denoted as y or
as f(x). Hence the coordinate of a generic point
P(x, y) on the graph is often denoted as (x, f(x)).
x
P=(x, f(x))
In order to be precise, basic geometric information
and formulas concerning graphs are given in
function notation.
y= f(x)
Slopes and the Difference Quotient
6. In order to be precise, basic geometric information
and formulas concerning graphs are given in
function notation.
x
P=(x, f(x))
y= f(x)
f(x)
Note that the f(x) = the height of the point at x.
Slopes and the Difference Quotient
Given x, the output of a function is denoted as y or
as f(x). Hence the coordinate of a generic point
P(x, y) on the graph is often denoted as (x, f(x)).
7. Let h be a small positive value,
so x+h is a point close to x,
In order to be precise, basic geometric information
and formulas concerning graphs are given in
function notation.
x
P=(x, f(x))
y= f(x)
f(x)
Note that the f(x) = the height of the point at x.
Slopes and the Difference Quotient
Given x, the output of a function is denoted as y or
as f(x). Hence the coordinate of a generic point
P(x, y) on the graph is often denoted as (x, f(x)).
8. x
P=(x, f(x))
Note that the f(x) = the height of the point at x.
Let h be a small positive value,
so x+h is a point close to x,
x+h
In order to be precise, basic geometric information
and formulas concerning graphs are given in
function notation.
f(x)
y= f(x)
Slopes and the Difference Quotient
h
Given x, the output of a function is denoted as y or
as f(x). Hence the coordinate of a generic point
P(x, y) on the graph is often denoted as (x, f(x)).
9. x
P=(x, f(x))
Note that the f(x) = the height of the point at x.
Let h be a small positive value,
so x+h is a point close to x,
x+h
then f(x+h) is the output for x+h,
and (x+h, f(x+h)) represents the
corresponding point, say Q,
on the graph.
In order to be precise, basic geometric information
and formulas concerning graphs are given in
function notation.
f(x)
y= f(x)
Slopes and the Difference Quotient
h
Given x, the output of a function is denoted as y or
as f(x). Hence the coordinate of a generic point
P(x, y) on the graph is often denoted as (x, f(x)).
10. x
P=(x, f(x))
Note that the f(x) = the height of the point at x.
Let h be a small positive value,
so x+h is a point close to x,
x+h
then f(x+h) is the output for x+h,
and (x+h, f(x+h)) represents the
corresponding point, say Q,
on the graph.
In order to be precise, basic geometric information
and formulas concerning graphs are given in
function notation.
Q=(x+h, f(x+h))
f(x)
y= f(x)
Slopes and the Difference Quotient
h
Given x, the output of a function is denoted as y or
as f(x). Hence the coordinate of a generic point
P(x, y) on the graph is often denoted as (x, f(x)).
11. x
P=(x, f(x))
Note that the f(x) = the height of the point at x.
Let h be a small positive value,
so x+h is a point close to x,
x+h
then f(x+h) is the output for x+h,
and (x+h, f(x+h)) represents the
corresponding point, say Q,
on the graph.
In order to be precise, basic geometric information
and formulas concerning graphs are given in
function notation.
Note that the f(x+h) = the height of the point at x + h.
Q=(x+h, f(x+h))
f(x)
f(x+h)
y= f(x)
Slopes and the Difference Quotient
h
Given x, the output of a function is denoted as y or
as f(x). Hence the coordinate of a generic point
P(x, y) on the graph is often denoted as (x, f(x)).
12. Recall that if (x1, y1) and (x2, y2)
are two points then the slope m
of the line connecting them is
Δy
m =
y2 – y1
= x2 – x1Δx
Slopes and the Difference Quotient
Δy
Δx
13. Recall that if (x1, y1) and (x2, y2)
are two points then the slope m
of the line connecting them is
Δy
m =
y2 – y1
= x2 – x1Δx x
P=(x, f(x))
x+h
Q=(x+h, f(x+h))
Slopes and the Difference Quotient
Δy
Δx
Let (x1,y1) = P = (x, f(x)) and (x2,y2) = Q = (x+h, f(x+h))
be two points on the graph of y = f(x) as shown,
14. Recall that if (x1, y1) and (x2, y2)
are two points then the slope m
of the line connecting them is
x
P=(x, f(x))
x+h
Q=(x+h, f(x+h))
Δy
m =
y2 – y1
= x2 – x1Δx
Δy
m = Δx
Slopes and the Difference Quotient
ΔyΔy
Δx
Let (x1,y1) = P = (x, f(x)) and (x2,y2) = Q = (x+h, f(x+h))
be two points on the graph of y = f(x) as shown, then
the slope of the cord connecting P and Q is
15. Recall that if (x1, y1) and (x2, y2)
are two points then the slope m
of the line connecting them is
x
P=(x, f(x))
x+h
Q=(x+h, f(x+h))
Δy
m =
y2 – y1
= x2 – x1Δx
Δy
m =
f(x+h) – f(x)
=Δx
Slopes and the Difference Quotient
ΔyΔy = f(x+h) – f(x)
Δx
Let (x1,y1) = P = (x, f(x)) and (x2,y2) = Q = (x+h, f(x+h))
be two points on the graph of y = f(x) as shown, then
the slope of the cord connecting P and Q is
16. Recall that if (x1, y1) and (x2, y2)
are two points then the slope m
of the line connecting them is
x
P=(x, f(x))
x+h
Q=(x+h, f(x+h))
Δy
m =
y2 – y1
= x2 – x1Δx
Δy
m =
f(x+h) – f(x)
= (x+h) – xΔx
Slopes and the Difference Quotient
ΔyΔy = f(x+h) – f(x)
Δx =h
Let (x1,y1) = P = (x, f(x)) and (x2,y2) = Q = (x+h, f(x+h))
be two points on the graph of y = f(x) as shown, then
the slope of the cord connecting P and Q is
17. Recall that if (x1, y1) and (x2, y2)
are two points then the slope m
of the line connecting them is
x
P=(x, f(x))
x+h
Q=(x+h, f(x+h))
Δy
m =
y2 – y1
= x2 – x1Δx
Δy
m =
f(x+h) – f(x)
= (x+h) – xΔx or m = f(x+h) – f(x)
h
Slopes and the Difference Quotient
Δy = f(x+h) – f(x)
Δx =h
Let (x1,y1) = P = (x, f(x)) and (x2,y2) = Q = (x+h, f(x+h))
be two points on the graph of y = f(x) as shown, then
the slope of the cord connecting P and Q is
18. Recall that if (x1, y1) and (x2, y2)
are two points then the slope m
of the line connecting them is
x
P=(x, f(x))
x+h
Q=(x+h, f(x+h))
Δy
m =
y2 – y1
= x2 – x1Δx
Let (x1,y1) = P = (x, f(x)) and (x2,y2) = Q = (x+h, f(x+h))
be two points on the graph of y = f(x) as shown, then
the slope of the cord connecting P and Q is
Δy
m =
f(x+h) – f(x)
= (x+h) – xΔx or m = f(x+h) – f(x)
h
f(x+h) – f(x) = Δy and h = (x+h) – x = Δx.
This is the "difference quotient“ version of the
slope–formula using the the function notation with
Slopes and the Difference Quotient
Δy = f(x+h) – f(x)
Δx =h
19. Example A:
a. Given f(x) = x2 – 2x + 2, find the slope of the cord
connecting the points (x, f(x)) and (x+h,f(x+h))
with x = 2 and h = 0.2. Draw the graph and the points.
Slopes and the Difference Quotient
20. Example A:
a. Given f(x) = x2 – 2x + 2, find the slope of the cord
connecting the points (x, f(x)) and (x+h,f(x+h))
with x = 2 and h = 0.2. Draw the graph and the points.
Slopes and the Difference Quotient
y = x2 – 2x + 2
21. Example A:
a. Given f(x) = x2 – 2x + 2, find the slope of the cord
connecting the points (x, f(x)) and (x+h,f(x+h))
with x = 2 and h = 0.2. Draw the graph and the points.
Slopes and the Difference Quotient
(2, 2)
2
y = x2 – 2x + 2
22. Example A:
a. Given f(x) = x2 – 2x + 2, find the slope of the cord
connecting the points (x, f(x)) and (x+h,f(x+h))
with x = 2 and h = 0.2. Draw the graph and the points.
We want the slope of the cord connecting the points
whose x-coordinates are x = 2 and x + h = 2 + h = 2.2.
Slopes and the Difference Quotient
(2.2, 2.44)
(2, 2)
2 2.2
y = x2 – 2x + 2
h=0.2
23. Example A:
a. Given f(x) = x2 – 2x + 2, find the slope of the cord
connecting the points (x, f(x)) and (x+h,f(x+h))
with x = 2 and h = 0.2. Draw the graph and the points.
f(x+h) – f(x)
h
Use the difference quotient,
the slope of the cord is
We want the slope of the cord connecting the points
whose x-coordinates are x = 2 and x + h = 2 + h = 2.2
Slopes and the Difference Quotient
(2.2, 2.44)
(2, 2)
2 2.2
y = x2 – 2x + 2
h=0.2
24. Example A:
a. Given f(x) = x2 – 2x + 2, find the slope of the cord
connecting the points (x, f(x)) and (x+h,f(x+h))
with x = 2 and h = 0.2. Draw the graph and the points.
f(x+h) – f(x)
h
Use the difference quotient,
the slope of the cord is
We want the slope of the cord connecting the points
whose x-coordinates are x = 2 and x + h = 2 + h = 2.2
f(2.2) – f(2)=
Slopes and the Difference Quotient
(2.2, 2.44)
(2, 2)
2 2.2
y = x2 – 2x + 2
h=0.2
25. Example A:
a. Given f(x) = x2 – 2x + 2, find the slope of the cord
connecting the points (x, f(x)) and (x+h,f(x+h))
with x = 2 and h = 0.2. Draw the graph and the points.
f(x+h) – f(x)
h
Use the difference quotient,
the slope of the cord is
We want the slope of the cord connecting the points
whose x-coordinates are x = 2 and x + h = 2 + h = 2.2
f(2.2) – f(2)=
Slopes and the Difference Quotient
(2.2, 2.44)
(2, 2)
2 2.2
y = x2 – 2x + 2
h=0.2
f(2.2)–f(2)
26. Example A:
a. Given f(x) = x2 – 2x + 2, find the slope of the cord
connecting the points (x, f(x)) and (x+h,f(x+h))
with x = 2 and h = 0.2. Draw the graph and the points.
f(x+h) – f(x)
h
Use the difference quotient,
the slope of the cord is
We want the slope of the cord connecting the points
whose x-coordinates are x = 2 and x + h = 2 + h = 2.2
f(2.2) – f(2)
0.2
=
Slopes and the Difference Quotient
(2.2, 2.44)
(2, 2)
2 2.2
y = x2 – 2x + 2
h=0.2
f(2.2)–f(2)
27. Example A:
a. Given f(x) = x2 – 2x + 2, find the slope of the cord
connecting the points (x, f(x)) and (x+h,f(x+h))
with x = 2 and h = 0.2. Draw the graph and the points.
f(x+h) – f(x)
h
Use the difference quotient,
the slope of the cord is
We want the slope of the cord connecting the points
whose x-coordinates are x = 2 and x + h = 2 + h = 2.2
f(2.2) – f(2)
0.2
=
Slopes and the Difference Quotient
(2.2, 2.44)
(2, 2)
2 2.2
y = x2 – 2x + 2
h=0.2
f(2.2)–f(2)
0.2
28. Example A:
a. Given f(x) = x2 – 2x + 2, find the slope of the cord
connecting the points (x, f(x)) and (x+h,f(x+h))
with x = 2 and h = 0.2. Draw the graph and the points.
f(x+h) – f(x)
h
Use the difference quotient,
the slope of the cord is
We want the slope of the cord connecting the points
whose x-coordinates are x = 2 and x + h = 2 + h = 2.2
f(2.2) – f(2)
0.2
=
=
2.44 – 2
0.2
Slopes and the Difference Quotient
(2.2, 2.44)
(2, 2)
2 2.2
y = x2 – 2x + 2
h=0.2
f(2.2)–f(2)
0.2
29. Example A:
a. Given f(x) = x2 – 2x + 2, find the slope of the cord
connecting the points (x, f(x)) and (x+h,f(x+h))
with x = 2 and h = 0.2. Draw the graph and the points.
f(x+h) – f(x)
h
Use the difference quotient,
the slope of the cord is
We want the slope of the cord connecting the points
whose x-coordinates are x = 2 and x + h = 2 + h = 2.2
f(2.2) – f(2)
0.2
=
=
2.44 – 2
0.2 =
0.44
0.2
Slopes and the Difference Quotient
(2.2, 2.44)
(2, 2)
2 2.2
y = x2 – 2x + 2
h=0.2
f(2.2)–f(2)
0.2
30. Example A:
a. Given f(x) = x2 – 2x + 2, find the slope of the cord
connecting the points (x, f(x)) and (x+h,f(x+h))
with x = 2 and h = 0.2. Draw the graph and the points.
f(x+h) – f(x)
h
Use the difference quotient,
the slope of the cord is
We want the slope of the cord connecting the points
whose x-coordinates are x = 2 and x + h = 2 + h = 2.2
f(2.2) – f(2)
0.2
=
=
2.44 – 2
0.2
= 2.2
=
0.44
0.2
Slopes and the Difference Quotient
(2.2, 2.44)
(2, 2)
2 2.2
y = x2 – 2x + 2
h=0.2
f(2.2)–f(2)
0.2
31. Example A:
a. Given f(x) = x2 – 2x + 2, find the slope of the cord
connecting the points (x, f(x)) and (x+h,f(x+h))
with x = 2 and h = 0.2. Draw the graph and the points.
f(x+h) – f(x)
h
Use the difference quotient,
the slope of the cord is
We want the slope of the cord connecting the points
whose x-coordinates are x = 2 and x + h = 2 + h = 2.2
f(2.2) – f(2)
0.2
=
=
2.44 – 2
0.2
= 2.2
=
0.44
0.2
Slopes and the Difference Quotient
(2.2, 2.44)
(2, 2)
2 2.2
y = x2 – 2x + 2
h=0.2
f(2.2)–f(2)
0.2
slope m = 2.2
32. b. Given f(x) = x2 – 2x + 2, simplify the formula for the
slope of the cord connecting the points (x, f(x)) and
(x+h, f(x+h)).
Slopes and the Difference Quotient
33. b. Given f(x) = x2 – 2x + 2, simplify the formula for the
slope of the cord connecting the points (x, f(x)) and
(x+h, f(x+h)).
We are to simplify the difference quotient formula
with f(x) = x2 – 2x + 2
Slopes and the Difference Quotient
34. b. Given f(x) = x2 – 2x + 2, simplify the formula for the
slope of the cord connecting the points (x, f(x)) and
(x+h, f(x+h)).
f(x+h) – f(x)
h
We are to simplify the difference quotient formula
with f(x) = x2 – 2x + 2
=
(x+h)2 – 2(x+h) + 2
h
Slopes and the Difference Quotient
35. b. Given f(x) = x2 – 2x + 2, simplify the formula for the
slope of the cord connecting the points (x, f(x)) and
(x+h, f(x+h)).
f(x+h) – f(x)
h
We are to simplify the difference quotient formula
with f(x) = x2 – 2x + 2
=
(x+h)2 – 2(x+h) + 2 – [ x2 – 2x + 2]
h
Slopes and the Difference Quotient
36. b. Given f(x) = x2 – 2x + 2, simplify the formula for the
slope of the cord connecting the points (x, f(x)) and
(x+h, f(x+h)).
f(x+h) – f(x)
h
We are to simplify the difference quotient formula
with f(x) = x2 – 2x + 2
=
(x+h)2 – 2(x+h) + 2 – [ x2 – 2x + 2]
h
2xh – 2h + h2
h
=
Slopes and the Difference Quotient
37. b. Given f(x) = x2 – 2x + 2, simplify the formula for the
slope of the cord connecting the points (x, f(x)) and
(x+h, f(x+h)).
f(x+h) – f(x)
h
We are to simplify the difference quotient formula
with f(x) = x2 – 2x + 2
=
(x+h)2 – 2(x+h) + 2 – [ x2 – 2x + 2]
h
2xh – 2h + h2
h
= 2x – 2 + h.=
Slopes and the Difference Quotient
38. *Another version of the difference
quotient formula is to use points
P = (a, f(a)) and Q= (b, f(b)),
b. Given f(x) = x2 – 2x + 2, simplify the formula for the
slope of the cord connecting the points (x, f(x)) and
(x+h, f(x+h)).
f(x+h) – f(x)
h
We are to simplify the difference quotient formula
with f(x) = x2 – 2x + 2
=
(x+h)2 – 2(x+h) + 2 – [ x2 – 2x + 2]
h
2xh – 2h + h2
h
= 2x – 2 + h.=
Slopes and the Difference Quotient
39. *Another version of the difference
quotient formula is to use points
P = (a, f(a)) and Q= (b, f(b)), we get
Δy
m =
f(b) – f(a)
= b – aΔx
b. Given f(x) = x2 – 2x + 2, simplify the formula for the
slope of the cord connecting the points (x, f(x)) and
(x+h, f(x+h)).
f(x+h) – f(x)
h
We are to simplify the difference quotient formula
with f(x) = x2 – 2x + 2
=
(x+h)2 – 2(x+h) + 2 – [ x2 – 2x + 2]
h
2xh – 2h + h2
h
= 2x – 2 + h.=
Slopes and the Difference Quotient
40. *Another version of the difference
quotient formula is to use points
P = (a, f(a)) and Q= (b, f(b)), we get
a
P=(a, f(a))
b
Q=(b, f(b))
Δy
m =
f(b) – f(a)
= b – aΔx
b. Given f(x) = x2 – 2x + 2, simplify the formula for the
slope of the cord connecting the points (x, f(x)) and
(x+h, f(x+h)).
f(x+h) – f(x)
h
We are to simplify the difference quotient formula
with f(x) = x2 – 2x + 2
=
(x+h)2 – 2(x+h) + 2 – [ x2 – 2x + 2]
h
2xh – 2h + h2
h
= 2x – 2 + h.=
Slopes and the Difference Quotient
41. *Another version of the difference
quotient formula is to use points
P = (a, f(a)) and Q= (b, f(b)), we get
a
P=(a, f(a))
b
Q=(b, f(b))
Δy
m =
f(b) – f(a)
= b – aΔx
b-a=Δx
f(b)–f(a) = Δy
b. Given f(x) = x2 – 2x + 2, simplify the formula for the
slope of the cord connecting the points (x, f(x)) and
(x+h, f(x+h)).
f(x+h) – f(x)
h
We are to simplify the difference quotient formula
with f(x) = x2 – 2x + 2
=
(x+h)2 – 2(x+h) + 2 – [ x2 – 2x + 2]
h
2xh – 2h + h2
h
= 2x – 2 + h.=
Slopes and the Difference Quotient
42. Example B:
a. Given f(x) = x2 – 2x + 2, find the slope of the cord
connecting the points (a, f(a)) and (b,f(b)) with a = 3
and b = 5.
Slopes and the Difference Quotient
43. Example B:
a. Given f(x) = x2 – 2x + 2, find the slope of the cord
connecting the points (a, f(a)) and (b,f(b)) with a = 3
and b = 5.
We want the slope of the cord connecting the points
whose x-coordinates are a = 3 and b = 5
Slopes and the Difference Quotient
44. Example B:
a. Given f(x) = x2 – 2x + 2, find the slope of the cord
connecting the points (a, f(a)) and (b,f(b)) with a = 3
and b = 5.
f(b) – f(a)
b – a
Using the formula, the slope of
the cord is
We want the slope of the cord connecting the points
whose x-coordinates are a = 3 and b = 5
Slopes and the Difference Quotient
45. Example B:
a. Given f(x) = x2 – 2x + 2, find the slope of the cord
connecting the points (a, f(a)) and (b,f(b)) with a = 3
and b = 5.
Using the formula, the slope of
the cord is
We want the slope of the cord connecting the points
whose x-coordinates are a = 3 and b = 5
f(5) – f(3)
5 – 3
=
Slopes and the Difference Quotient
f(b) – f(a)
b – a
46. Example B:
a. Given f(x) = x2 – 2x + 2, find the slope of the cord
connecting the points (a, f(a)) and (b,f(b)) with a = 3
and b = 5.
Using the formula, the slope of
the cord is
We want the slope of the cord connecting the points
whose x-coordinates are a = 3 and b = 5
f(5) – f(3)
5 – 3
=
=
17 – 5
2
Slopes and the Difference Quotient
f(b) – f(a)
b – a
47. Example B:
a. Given f(x) = x2 – 2x + 2, find the slope of the cord
connecting the points (a, f(a)) and (b,f(b)) with a = 3
and b = 5.
Using the formula, the slope of
the cord is
We want the slope of the cord connecting the points
whose x-coordinates are a = 3 and b = 5
f(5) – f(3)
5 – 3
=
=
17 – 5
2
= 6=
12
2
Slopes and the Difference Quotient
f(b) – f(a)
b – a
48. Example B:
a. Given f(x) = x2 – 2x + 2, find the slope of the cord
connecting the points (a, f(a)) and (b,f(b)) with a = 3
and b = 5.
Using the formula, the slope of
the cord is
We want the slope of the cord connecting the points
whose x-coordinates are a = 3 and b = 5
f(5) – f(3)
5 – 3
=
=
17 – 5
2
= 6
(5, 17)
(3, 5)
3 5=
12
2
Slopes and the Difference Quotient
f(b) – f(a)
b – a
49. Example B:
a. Given f(x) = x2 – 2x + 2, find the slope of the cord
connecting the points (a, f(a)) and (b,f(b)) with a = 3
and b = 5.
Using the formula, the slope of
the cord is
We want the slope of the cord connecting the points
whose x-coordinates are a = 3 and b = 5
f(5) – f(3)
5 – 3
=
=
17 – 5
2
= 6
(5, 17)
(3, 5)
3 5=
12
2
12
2
slope m = 6
Slopes and the Difference Quotient
f(b) – f(a)
b – a
50. b. Given f(x) = x2 – 2x + 2, simplify the difference
quotient slope of the cord connecting the points
(a, f(a)) and (b, f(b)).
(b, f(b))
(a, f(a))
a b
f(b)-f(a)
b-a
Slopes and the Difference Quotient
51. b. Given f(x) = x2 – 2x + 2, simplify the difference
quotient slope of the cord connecting the points
(a, f(a)) and (b, f(b)).
f(b) – f(a)
b – a
We are to simplify the 2nd form of the difference
quotient formula with f(x) = x2 – 2x + 2
(b, f(b))
(a, f(a))
a b
f(b)-f(a)
b-a
Slopes and the Difference Quotient
52. b. Given f(x) = x2 – 2x + 2, simplify the difference
quotient slope of the cord connecting the points
(a, f(a)) and (b, f(b)).
f(b) – f(a)
b – a
We are to simplify the 2nd form of the difference
quotient formula with f(x) = x2 – 2x + 2
=
b2 – 2b + 2 – [ a2 – 2a + 2]
b – a
(b, f(b))
(a, f(a))
a b
f(b)-f(a)
b-a
Slopes and the Difference Quotient
53. b. Given f(x) = x2 – 2x + 2, simplify the difference
quotient slope of the cord connecting the points
(a, f(a)) and (b, f(b)).
f(b) – f(a)
b – a
We are to simplify the 2nd form of the difference
quotient formula with f(x) = x2 – 2x + 2
=
b2 – 2b + 2 – [ a2 – 2a + 2]
b – a
=
b2 – a2 – 2b + 2a
b – a
(b, f(b))
(a, f(a))
a b
f(b)-f(a)
b-a
Slopes and the Difference Quotient
54. b. Given f(x) = x2 – 2x + 2, simplify the difference
quotient slope of the cord connecting the points
(a, f(a)) and (b, f(b)).
f(b) – f(a)
b – a
We are to simplify the 2nd form of the difference
quotient formula with f(x) = x2 – 2x + 2
=
b2 – 2b + 2 – [ a2 – 2a + 2]
b – a
=
b2 – a2 – 2b + 2a
b – a
= (b – a)(b + a) – 2(b – a)
b – a
(b, f(b))
(a, f(a))
a b
f(b)-f(a)
b-a
Slopes and the Difference Quotient
55. b. Given f(x) = x2 – 2x + 2, simplify the difference
quotient slope of the cord connecting the points
(a, f(a)) and (b, f(b)).
f(b) – f(a)
b – a
We are to simplify the 2nd form of the difference
quotient formula with f(x) = x2 – 2x + 2
=
b2 – 2b + 2 – [ a2 – 2a + 2]
b – a
=
b2 – a2 – 2b + 2a
b – a
= (b – a)(b + a) – 2(b – a)
b – a
= (b – a) [(b + a) – 2]
b – a
(b, f(b))
(a, f(a))
a b
f(b)-f(a)
b-a
Slopes and the Difference Quotient
56. b. Given f(x) = x2 – 2x + 2, simplify the difference
quotient slope of the cord connecting the points
(a, f(a)) and (b, f(b)).
f(b) – f(a)
b – a
We are to simplify the 2nd form of the difference
quotient formula with f(x) = x2 – 2x + 2
=
b2 – 2b + 2 – [ a2 – 2a + 2]
b – a
=
b2 – a2 – 2b + 2a
b – a
= (b – a)(b + a) – 2(b – a)
b – a
= (b – a) [(b + a) – 2]
b – a
= b + a – 2
(b, f(b))
(a, f(a))
a b
f(b)-f(a)
b-a
Slopes and the Difference Quotient
57. HW
Given the following f(x), x, and h find f(x+h) – f(x)
1. y = 3x+2, x= 2, h = 0.1 2. y = -2x + 3, x= -4, h = 0.05
3. y = 2x2 + 1, x = 1, h = 0.1 4. y = -x2 + 3, x= -2, h = -0.2
Given the following f(x), simplify Δy = f(x+h) – f(x)
5. y = 3x+2 6. y = -2x + 3
7. y = 2x2 + 1 8. y = -x2 + 3
Simplify the difference quotient
f(x+h) – f(x)
h
of the following functions
9. y = -4x + 3 10. y = mx + b
11. y = 3x2 – 2x +2 12. y = -2x2 + 3x -1
13 – 16, simplify the difference quotient
f(b) – f(a)
b – a
of the given functions.
Slopes and the Difference Quotient