What Makes the Standard Deviation Larger or Smaller?
You will find 15 pairs of graphs on the next four pages. The mean for each graph () is given just
above each histogram. For each pair of graphs presented below
1. Indicate whether one of the graphs has
Name_
Class Period_
Decay of Skittleium
Introduction:
The decay of radioactive isotopes creates interesting data. The isotope Skittleium is commonly found in
vending machines throughout the world. The final decay elements of Skittleium are Skittles. We wi
Name (s): _
Fair?
Are Pennies
Pennies Lab (10 Points, to be emailed to
jpage@livingston.org)
People often flip a coin to make a random selection between
two options. However, the randomness depends on the assumption
that the probability of getting heads i
HOW GOOD IS THE FIT?
M&Ms Lab
STATISTICS Chi-Squared Test
(Chapter 13)
Students Will:
Gather their own data regarding the frequency of the colors of
M&Ms in a package by counting the number of M&Ms in their pack
of candy.
Compute the expected number of
APStatisticsUnitI
Date:
UNIT I Organizing Data
1.2 Describing Distributions with Numbers
Measuring Center
Mean arithmetic average
Sensitive to the influence of extreme observations, therefore is NOT resistant. Resistant is one of the words
to remember. Ex
Statistics
Ch. 2
Practice Test
Name:
Directions: Work on these sheets. You may use your standard normal table.
Part 1: Multiple Choice. Circle the letter corresponding to the best answer.
1. The heights of American men aged 18 to 24 are approximately norm
First, lets review Lurking Variable A lurking variable is a variable that has an
important effect on the relationship among the variables in a study but is not included
among the variables studied. THE KEY IS THAT THEY ARE SO HIDDEN, YOU DID
NOT EVEN THIN
Lurking Variables and Confounding Variables
Students in introductory Statistics classes often are confused by the terms above, and
perhaps for good reason. Instead of fumbling through my own definition, I will copy a
post from Dr. David Moore, perhaps one
Statistics
Practice Test
Chapter 5
Name:_
Date:_Period:_
Chapter 5:Practice Test
Part 1: Multiple Choice. (2 points each)
Hand write the letter corresponding to the best answer in space provided on page 6.
_1. Which one of the following is not a principle
Random Variables
Section 7.1
Discrete and Continuous
Random Variables
random variable x represents the numerical values
associated with the possible outcomes of a probability
experiment
BOOK DEF:A random variable is a variable whose value is a
numerical o
Chapter 13 Overview
Definition of IRONY: difference between actual (observed) results and expected results.
Our new distribution.new shapenew calculations.same principle
2
Some Basics: The chi-square (? )
distribution is NOT symmetric like the
normal curv
Chapter 13: Inference for Tables
Key Vocabulary:
chi-square test for goodness of fit
segmented bar chart
chi-square statistic
expected count
observed count
degrees of freedom
chi-square distribution
components of chi-square
cell counts
r x c table
cell
Ca
Chapter 13
13.1 Goodness of fit
Objective: To assess whether the Key Club representation is as stated by Mr. Page.
Claim: Freshman account for 20% of the Key Club membership, Sophomores 20%,
Juniors 40%, and Seniors 20%.
SRS: (random sample of NJ high sch
Chi-Squared Tests
Test of Independence
Population: M&Ms, mixed assortment of different types of M&Ms, dark chocolate, pretzel, and
milk chocolate
Parameter: The color distribution for the different types of M&Ms.
Ho: Color and type of M&M are independent.
Inference for Slope
Well, now that we can describe the linear relationship between two quantitative variables, it's
time to conduct inference.
The Big Idea
There are several parameters in linear regression. The big idea is that there is a real linear
rela