Let me tell you about some of the important things Ive learned about cells. First, Ill start with
I learned about how the cell starts with the centrosome and how it organizes the cytoskeleton. I
learn
To the Student
Statistical Thinking and You
The purpose of this book is to give you a working knowledge of the big ideas of statistics and
of the methods used in solving statistical problems. Because
Part 1: Analysis of Data
Mrs. K Data Analysis:
Total Mean Score: 3.54
Standard Deviation: 1.46
Median Score: 4
Min: 1
Max: 5
First quartile: 2
Third quartile: 5
Outliers: N/A
The data is skewed to the
Dear Mr. Taylor
Counterfeit coins are a problem that vending machine mechanics have dealt with since the rise
of the vending machine. For many, a counterfeit coin comes in the form of an arcade token
Pre-Calculus Semester 1
Formulas
Polynomials
Given the polynomial equation
ax 2 bx c 0
b b 2 4ac
x
2a
discriminant is
b 2 4ac
Given the polynomial function
Average Rate of Change
Given a function
y f
Intended Christmas Gift Spending Over Time
For our topic we chose to research the amount of money that U.S. consumers intended
to spend each year on Christmas gifts and how it changes every year. We b
Background:
M&Ms are a delicious candy-coated chocolate snack that many people all over the world
enjoy. There are many different kinds of these snacks currently on the market.
Including, but not limi
Chapter 7
7.1 Distributions of Samples
Parameter
o Numerical characteristic about the population. Typically the value is unknown
1. , p, squiggly squared, regular square
o Statistic1.
Characteristic
Chapter 5
Probability Language 5.1
Empirical Probability: Probability obtained through observation
Law of Large Numbers (of trials): Chance behavior is unpredictable in the short run but a predictable
Chapter 2
Chapter 2.1 A Closer Look at Percentiles
Pt. 1
Pn = Value of Data where at least n% of the date fall below this value
P8 = 22nd score
.08 x 267 - 21.36
Discrete Data
% x n = Location of the
Chapter 1: Exploring Data
Introduction: Data Analysis: Making Sense of Data and 1.1 Categorical vs.
Quantitative Data
Vocabulary
Individuals: objects described by a set of data. Ex: people, animals, o