Precalculus Camp

This course explores the basic properties of functions, conic sections, matrices and determinants, introductory trigonometry,and probability. It weaves together algebra, geometry, and mathematical functions in order to prepare one for Calculus.

15 topics

337 lectures

Educators

LL

Camp Curriculum

40 videos

Powers and Polynomial

25 videos

Rational Numbers

11 videos

41 videos

Exponential Functions

15 videos

61 videos

Parametric Equations

5 videos

Introduction to Vectors

15 videos

15 videos

Polar Coordinates

5 videos

30 videos

Introduction to Conic Sections

23 videos

15 videos

Introduction to Combinatorics and Probability

16 videos

Introduction to Sequences and Series

20 videos

Lectures

Introduction to Combinatorics and Probability

Independent Vs Dependent - Overview

In statistics, dependence or association is any statistical relationship, whether causal or not, between two random variables or bivariate data. Familiar examples of dependent phenomena include the correlation between the physical statures of parents and their offspring, and the correlation between the demand for a product and its price. Many pairs of random variables are correlated, but in the absence of a causal relationship, this correlation is due to chance. For example, a study of the heights of parents and their children might show that pairs of individuals have a correlation of 0.7 for height, meaning that if the parent is 70 inches tall, the child is also on average 70 inches tall. This does not imply that parental height caused the child's height; both are usually caused by a common factor.

Introduction to Combinatorics and Probability

Independent Vs Dependent - Example 1

In statistics, dependence or association is any statistical relationship, whether causal or not, between two random variables or bivariate data. Familiar examples of dependent phenomena include the correlation between the physical statures of parents and their offspring, and the correlation between the demand for a product and its price. Many pairs of random variables are correlated, but in the absence of a causal relationship, this correlation is due to chance. For example, a study of the heights of parents and their children might show that pairs of individuals have a correlation of 0.7 for height, meaning that if the parent is 70 inches tall, the child is also on average 70 inches tall. This does not imply that parental height caused the child's height; both are usually caused by a common factor.

Introduction to Combinatorics and Probability

Independent Vs Dependent - Example 2

In statistics, dependence or association is any statistical relationship, whether causal or not, between two random variables or bivariate data. Familiar examples of dependent phenomena include the correlation between the physical statures of parents and their offspring, and the correlation between the demand for a product and its price. Many pairs of random variables are correlated, but in the absence of a causal relationship, this correlation is due to chance. For example, a study of the heights of parents and their children might show that pairs of individuals have a correlation of 0.7 for height, meaning that if the parent is 70 inches tall, the child is also on average 70 inches tall. This does not imply that parental height caused the child's height; both are usually caused by a common factor.

Introduction to Combinatorics and Probability

Independent Vs Dependent - Example 3

In statistics, dependence or association is any statistical relationship, whether causal or not, between two random variables or bivariate data. Familiar examples of dependent phenomena include the correlation between the physical statures of parents and their offspring, and the correlation between the demand for a product and its price. Many pairs of random variables are correlated, but in the absence of a causal relationship, this correlation is due to chance. For example, a study of the heights of parents and their children might show that pairs of individuals have a correlation of 0.7 for height, meaning that if the parent is 70 inches tall, the child is also on average 70 inches tall. This does not imply that parental height caused the child's height; both are usually caused by a common factor.

Introduction to Combinatorics and Probability

Independent Vs Dependent - Example 4

In statistics, dependence or association is any statistical relationship, whether causal or not, between two random variables or bivariate data. Familiar examples of dependent phenomena include the correlation between the physical statures of parents and their offspring, and the correlation between the demand for a product and its price. Many pairs of random variables are correlated, but in the absence of a causal relationship, this correlation is due to chance. For example, a study of the heights of parents and their children might show that pairs of individuals have a correlation of 0.7 for height, meaning that if the parent is 70 inches tall, the child is also on average 70 inches tall. This does not imply that parental height caused the child's height; both are usually caused by a common factor.

Introduction to Combinatorics and Probability

Independent Vs Dependent - Example 5

In statistics, dependence or association is any statistical relationship, whether causal or not, between two random variables or bivariate data. Familiar examples of dependent phenomena include the correlation between the physical statures of parents and their offspring, and the correlation between the demand for a product and its price. Many pairs of random variables are correlated, but in the absence of a causal relationship, this correlation is due to chance. For example, a study of the heights of parents and their children might show that pairs of individuals have a correlation of 0.7 for height, meaning that if the parent is 70 inches tall, the child is also on average 70 inches tall. This does not imply that parental height caused the child's height; both are usually caused by a common factor.

Introduction to Combinatorics and Probability

Mutually Exclusive - Overview

In mathematics, a set of objects is mutually exclusive if it is impossible for more than one object to be an element of the set at the same time. For example, the numbers 2, 3, and 4 are mutually exclusive, because no number can be in all three sets at the same time.

Introduction to Combinatorics and Probability

Mutually Exclusive - Example 1

In mathematics, a set of objects is mutually exclusive if it is impossible for more than one object to be an element of the set at the same time. For example, the numbers 2, 3, and 4 are mutually exclusive, because no number can be in all three sets at the same time.

Introduction to Combinatorics and Probability

Mutually Exclusive - Example 2

In mathematics, a set of objects is mutually exclusive if it is impossible for more than one object to be an element of the set at the same time. For example, the numbers 2, 3, and 4 are mutually exclusive, because no number can be in all three sets at the same time.

Introduction to Combinatorics and Probability

Mutually Exclusive - Example 3

In mathematics, a set of objects is mutually exclusive if it is impossible for more than one object to be an element of the set at the same time. For example, the numbers 2, 3, and 4 are mutually exclusive, because no number can be in all three sets at the same time.

Introduction to Combinatorics and Probability

Mutually Exclusive - Example 4

In mathematics, a set of objects is mutually exclusive if it is impossible for more than one object to be an element of the set at the same time. For example, the numbers 2, 3, and 4 are mutually exclusive, because no number can be in all three sets at the same time.

Introduction to Combinatorics and Probability

Mutually Exclusive - Example 5

In mathematics, a set of objects is mutually exclusive if it is impossible for more than one object to be an element of the set at the same time. For example, the numbers 2, 3, and 4 are mutually exclusive, because no number can be in all three sets at the same time.

Introduction to Combinatorics and Probability

Probability With Combinations - Overview

In mathematics, a combination is a way to select items from a collection, such as a set or a deck of cards.

Introduction to Combinatorics and Probability

Probability With Combinations - Example 1

In mathematics, a combination is a way to select items from a collection, such as a set or a deck of cards.

Introduction to Combinatorics and Probability

Probability With Combinations - Example 2

In mathematics, a combination is a way to select items from a collection, such as a set or a deck of cards.

Introduction to Combinatorics and Probability

Probability With Combinations - Example 3

In mathematics, a combination is a way to select items from a collection, such as a set or a deck of cards.