Lecture 1: Basic Differentiation Rules
The Power Rule
- If $y = ax^n$, then its derivative is: $\frac{dy}{dx} = n \cdot a \cdot x^{n-1}$
Sum and Difference Rules
- $\frac{d}{dx}[f(x) \pm g(x)] = f'(x) \pm g'(x)$
The Product Rule
- $\frac{dy}{dx} = u \frac{dv}{dx} + v \frac{du}{dx}$
The Quotient Rule
- $\frac{dy}{dx} = \frac{v \frac{du}{dx} - u \frac{dv}{dx}}{v^2}$
The Chain Rule
- $\frac{dy}{dx} = \frac{dy}{du} \cdot \frac{du}{dx}$
Lecture 2: Trigonometric and Logarithmic Functions
Derivatives of Trigonometric Functions
- $\frac{d}{dx}(\sin x) = \cos x$
- $\frac{d}{dx}(\cos x) = -\sin x$
- $\frac{d}{dx}(\tan x) = \sec^2 x$
Derivatives of Inverse Trigonometric Functions
- $\frac{d}{dx}(\sin^{-1} u) = \frac{u'}{\sqrt{1-u^2}}$
- $\frac{d}{dx}(\tan^{-1} u) = \frac{u'}{1+u^2}$
Derivatives of Exponential and Logarithmic Functions
- $\frac{d}{dx}(e^u) = e^u \cdot u'$
- $\frac{d}{dx}(\ln u) = \frac{1}{u} \cdot u'$
Lecture 3: Hyperbolic Functions and Applications
Derivatives of Hyperbolic Functions
- $\frac{d}{dx}(\sinh x) = \cosh x$
- $\frac{d}{dx}(\cosh x) = \sinh x$
- $\frac{d}{dx}(\tanh x) = \text{sech}^2 x$
Derivatives of Inverse Hyperbolic Functions
- $\frac{d}{dx}(\sinh^{-1} u) = \frac{u'}{\sqrt{u^2+1}}$
- $\frac{d}{dx}(\tanh^{-1} u) = \frac{u'}{1-u^2}$
Lecture 4: L'Hôpital's Rule and Series
L'Hôpital's Rule
- For limits of indeterminate forms like $\frac{0}{0}$ or $\frac{\infty}{\infty}$: $\lim_{x \to c} \frac{f(x)}{g(x)} = \lim_{x \to c} \frac{f'(x)}{g'(x)}$
Taylor and Maclaurin Series
- A Maclaurin series is a Taylor series when $a=0$: $f(x) = \sum_{n=0}^{\infty} \frac{f^{(n)}(0)}{n!}x^n$
Matrices
Matrix Operations
- Operations: Matrices of the same size can be added. For multiplication $A \cdot B$, the number of columns in $A$ must equal the number of rows in $B$. [29]
- Transpose ($A^T$): Interchange rows and columns. [29]
- Determinant: For $A = \begin{pmatrix} a & b \\ c & d \end{pmatrix}$, $\det(A) = ad - bc$. For a 3x3 matrix, the determinant can be found by expanding along a row or column using cofactors. [4, 6]
- Inverse: $A^{-1} = \frac{1}{\det(A)} \text{adj}(A)$. An inverse exists only if $\det(A) \neq 0$. [1, 10]
Gauss-Jordan Elimination
- Goal: To solve a system of linear equations by transforming its augmented matrix into reduced row-echelon form using elementary row operations. [2, 3]
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Reduced Row-Echelon Form:
- All rows with only zero entries are at the bottom.
- The leading entry (pivot) of each non-zero row is 1.
- Each pivot is the only non-zero entry in its column.
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Elementary Row Operations:
- Swapping two rows.
- Multiplying a row by a non-zero constant.
- Adding a multiple of one row to another row. [14]
Interactive Math Quiz (75 Questions)
Test your understanding of calculus and matrices with a comprehensive set of questions, including challenging problems and Gauss-Jordan elimination. You can navigate between questions using the 'Next' and 'Previous' buttons.