Lab Assignment #8
Math 338
Fall, 2016
Due Sunday (10/9)
Part I. Means for Normals
A central idea in Statistics is the notion of sampling variability. Specifically, we have noted how a
sample estimate
Lab Assignment #5
Math 338
Fall 2016
Due Thursday (09/29)
Part I. Means for Normals
A central idea in Statistics is the notion of sampling variability. Specifically, we have notes how a
sample estimat
Bliss (1952) was interested in the effect of Vitamin C on tooth growth in guinea pigs. The data from this
study can be found in the toothgrowth file on Titanium. Upload this data to Rguroo.
Numerical
Notes
MATH 338: Statistics Applied to the Natural
Sciences
Midterm 1 Review Questions
Department of Mathematics, California State University, Fullerton
Fall 2016
1 / 16
Notes
The personal department k
Chapter 9 Practice Free Response
1. A certain beverage company is suspected of underfilling its cans of soft drink. The
company advertises that its cans contain, on the average, 12 ounces of soda with
10.2 More Detail About
Simple Linear Regression
Analysis of variance for regression
The ANOVA F test
1
Analysis of Variance for Regression
The regression model is:
Data =
fit
+
y i = ( 0 + 1 x i) +
Analysis of Variance for Regression
10.2 More Detail About
Simple Linear Regression
The regression model is:
! Analysis of variance for regression
Data =
! The ANOVA F test
fit
+
error
yi = (0 + 1xi)
Cong Le
Math 338
Lab Assignment #2
Part I. Relapse Data Set
The data below describe the time to relapse (in months) for patients who suffer
from acute leukemia (Freireich et. al., 1963):
1, 22, 3, 12,
Chapter 3
Exploratoryanalysisalonecanrarely(never,rarely,usually,
always)provideconvincingevidenceforitsconclusions,because
strikingpatternscouldarisefrommanydifferentsources.
Availabledata are data t
CWID: ELISE %
Phys-2 1 1 Midterm
March 23, 2017
CONCEPTUAL QUESTIONS 65 points (6.5 points each)
Question 1
The graph accompanying this problem shows a three-part motion. For each of the three parts,
Regression Line
2.4 Least-Squares Regression
!
!Regression lines
!Least-squares regression line
If correlation measures the direction and strength of the
linear relationship between two quantitative v
Friday, May 5, 2017
Math 338
Name:
Quiz 8
Spring 2017
We will consider a dataset collected over a variety of states with the following variables:
Life Exp: life expectancy in years (196971)
Income: pe
Section 7.1. The ImpulseMomentum Theorem
2. A model rocket is constructed with a motor that can provide a total impulse of 29.0 N s. The
mass of the rocket is 0.175 kg. What is the speed that this roc
Introduction
10.1 Simple Linear
Regression
When a scatterplot shows a linear relationship between a quantitative
explanatory variable x and a quantitative response variable y, we can use
the least-squ
Random Variables
Discrete Random Variables:
Parts of Section 4.3 and 4.4
From Section 4.2, we learned a probability model describes the
possible outcomes of a chance process and the likelihood that th
Variables
1.2 Displaying Distributions
with Graphs
Key terms:
! Variables
Exploring Data
! Examining distributions of variables
! Graphs for categorical variables
! Bar graphs
! Pie charts
!
Begin by
Sampling Distributions
3.4 Toward Statistical
Inference
!Parameters and statistics
3.4 Toward Statistical Inference
!Sampling variability
4.4 Statistical Estimation and the Law of Large
Numbers
!Sampl
1.4 Density Curves and
Normal Distributions
Continuous Random Variables:
Parts of Section 4.3 and
Section 1.4
!Density curves
!Measuring center and spread for density curves
Section 4.3: Random variab
The Idea of Probability
Outline for Probability
and
the Normal Distribution
Chance behavior is unpredictable in the short run, but has a regular and
predictable pattern in the long run.
Week 3: Sectio
Chapter 3
Producing Data
3.1 Sources of Data
! Anecdotal data
Introduction
! Available data
3.1 Sources of Data
! Sample surveys and experiments
3.2 Design of Experiments
! Observation vs. experiment
Sampling Distributions
5.1 The Sampling Distribution
of a Sample Mean
3.4 Toward Statistical Inference
! The mean and standard deviation of the sample mean
4.4 Statistical Estimation and the Law of La
1.3 Describing Distributions
with Numbers
1.3 Describing Distributions
with Numbers
Key terms:
From graphical to numerical descriptions of data.
!Measures of center: mean, median
Graphical visual impr
Chapter 6
Introduction to Inference
6.1 Estimating with
Confidence
! Inference
6.1 Estimating with Confidence
! Statistical confidence
6.2 Tests of Significance
! Confidence intervals
6.3 Use and Abus
Population and Sample
3.3 Sampling Design
The population in a statistical study is the entire group of individuals
about which we want information.
!Population and sample
A sample is the part of the p
Chapter 2
Looking at Data
Relationships
2.1 Relationships
Goal: Explore the relationship between two
variables (specifically, the linear relationship).
2.1 Relationships
! What is an association betwe
Sampling Distributions
4.4 Statistical Estimation and
the Law of Large Numbers
(pg. 267)
3.4 Toward Statistical Inference
! The law of large numbers
4.4 Statistical Estimation and the Law of Large
Num
Two types of errors
6.4 Power and Inference as a
Decision
When we draw a conclusion from a significance test, we hope our
conclusion will be correct. But sometimes it will be wrong. There are two
type
Name:
Math 338
Exam 1 Lab
Spring 2017
Use R to answer the following questions. You need to include both the R-codes and
the results. Each question should be on one page of paper.
Your answers should l
Mechelle Cabral
DC vs Marvel
Over the past few decades movies have evolved and become a forefront of pop-culture in
the United States and even the world. From watching hilarious animated children movi
Math 338 Lecture
Notes
Summer 2017
Lectures 1-4: Toward Inference
How Research Works
1. Make a claim, or ask a question,
about the real world
Real World
4. State the results of the
analysis in the con
Lab Assignment #11
Math 338
Summer, 2017
Due Monday (07/31)
Part I. Probability and Relative Frequency
Suppose a random experiment is repeated many times, for example, a fair coin is flipped 1000
time
Math 338 Lecture
Notes
Summer 2017
Lectures 5-9: Statistical Inference for One Quantitative Variable
What is Inference?
Statistical inference is the process of making conclusions about data
Most of
Math 338 Lecture
Notes
Summer 2017
Lectures 10-13: Relationships Between Quantitative Variables
Association
Two variables measured on the same cases are associated if knowing the values
of one variab