Algebra Basics Quiz

Definition: Branch of mathematics dealing with symbols and rules for manipulating those symbols.
Key Concepts:
- Variables: Symbols that represent numbers (e.g., x, y).
- Expressions: Combinations of variables and constants (e.g., 3x + 2).
- Equations: Statements that two expressions are equal (e.g., 2x + 3 = 7).
- Functions: Relationships between inputs and outputs (e.g., f(x) = x^2).
Types of Equations:
- Linear Equations: Equations of the first degree (e.g., y = mx + b).
- Quadratic Equations: Equations of the second degree (e.g., ax^2 + bx + c = 0).
- Polynomial Equations: Equations involving polynomials.
Operations:
- Factoring: Breaking down expressions into products (e.g., x^2 - 9 = (x - 3)(x + 3)).
- Solving: Finding the values of variables that satisfy the equation.

Definition: Branch of mathematics that studies continuous change.
Key Concepts:
- Limits: The value that a function approaches as the input approaches a certain point.
- Derivatives: Measure the rate of change of a function (e.g., f'(x) = lim(h→0) [(f(x+h) - f(x)) / h]).
- Integrals: Measure the accumulation of quantities (e.g., ∫f(x)dx represents the area under the curve of f(x)).
Fundamental Theorem of Calculus:
- Connects differentiation and integration, stating that differentiation and integration are inverse processes.
Applications:
- Used in physics, engineering, economics for optimization, motion analysis, area calculations, etc.

Definition: Study of data collection, analysis, interpretation, presentation, and organization.
Key Concepts:
- Descriptive Statistics: Summarizes and describes features of a dataset (e.g., mean, median, mode).
- Inferential Statistics: Makes inferences and predictions about a population based on a sample.
Types of Data:
- Qualitative: Non-numerical data (e.g., colors, names).
- Quantitative: Numerical data (e.g., height, weight).
Common Measures:
- Mean: Average value.
- Median: Middle value when arranged in order.
- Variance: Measure of data dispersion from the mean.
- Standard Deviation: Square root of variance, indicates average distance from the mean.
Probability: Study of uncertainty, foundational to inferential statistics.

Branch of mathematics focused on symbols and rules for manipulating those symbols.
Variables: Symbols (such as x, y) representing unknown numbers.
Expressions: Combinations of variables and constants, exemplified by 3x + 2.
Equations: Statements indicating equality between two expressions, like 2x + 3 = 7.
Functions: Describe relationships between an input and an output, e.g., f(x) = x².
Linear Equations: First-degree equations that can be represented in the form y = mx + b.
Quadratic Equations: Second-degree equations typically written as ax² + bx + c = 0.
Polynomial Equations: Equations that involve polynomials with varying degrees.
Factoring: The process of breaking down expressions into products, illustrated by x² - 9 = (x - 3)(x + 3).
Solving: Involves determining the variable values that satisfy a given equation.

Branch of mathematics studying continuous change.
Limits: Values that a function approaches as inputs get closer to a specific point.
Derivatives: Quantify the rate of change of a function, represented mathematically as f'(x) = lim(h→0) [(f(x+h) - f(x)) / h].
Integrals: Represent accumulation of quantities, with ∫f(x)dx indicating the area under the curve of f(x).
Fundamental Theorem of Calculus: Establishes the connection between differentiation and integration as inverse processes.
Applications include use in physics, engineering, and economics for tasks like optimization and motion analysis.

Focuses on data collection, analysis, interpretation, presentation, and organization.
Descriptive Statistics: Summarizes dataset features through values such as mean, median, and mode.
Inferential Statistics: Draws conclusions and makes predictions about a population based on sample data.
Types of Data:
- Qualitative Data: Non-numerical, including categories like colors and names.
- Quantitative Data: Numerical forms such as height and weight.
Common Measures:
- Mean: The average value calculated from a dataset.
- Median: The middle value of an ordered dataset.
- Variance: Indicates how much data disperses from the mean.
- Standard Deviation: The square root of variance, reflecting average distance of data points from the mean.
Probability: Fundamental to inferential statistics, it addresses uncertainty within datasets.