Index

A^c

Introduction

H₀

Introduction

H_A

Introduction

Q₁

The 5 Basic Descriptive | Parameters

Q₃

The 5 Basic Descriptive | Parameters

R²

Relationships Between Variables, Part

s

Measures of Scale | Parameters

s²

Measures of Scale

$\hat{p}$

Introduction

$\mu$

Parameters

$\sigma$

More Parameters

$\sigma^2$

More Parameters

$\lambda$

Poisson Probability Model

$\theta$

Parameters

$\sigma$

Parameters

$\mu$

Empirical Rule

$\bar{x}$

Some Probability Examples

$\theta$

Confidence Intervals Based on

$\Delta$

Introduction

$\bar{x}$

Measures of Center

accept

A Testing Procedure

adjacent points

Outliers and Box Plots

alternative hypothesis

Introduction

asymmetric

Sample Distributions for Continuous | Sample Distributions for Continuous

bell shaped

Normal Distribution

Bernoulli

Binomial Probability Model

bi-modal

Sample Distributions for Continuous

bin(n,p)

Binomial Probability Model

binomial

Binomial Probability Model

random variable

Binomial Probability Model

bootstrap

Confidence Intervals Based on

cause and effect

Introduction

central limit theorem

Normal Distribution | Some Probability Examples | Central Limit Theorem

coefficient of determination

Relationships Between Variables, Part

complement

Introduction

completely randomized design

Completely Randomized Designs

conditional probability

Independence

confidence interval

Confidence Intervals for Means | Confidence Intervals for Proportions

based on resampling

Confidence Intervals Based on

mean

Confidence Intervals for Means

median

Confidence Intervals Based on

proportion

Confidence Intervals for Proportions

continuous data

Introduction | Sample Distributions for Continuous

continuous random variable

Random Variables

controlled experiment

Introduction | Completely Randomized Designs

controlled regression design

Regression Experimental Designs

covariance

Measures of Scale

CRD

Completely Randomized Designs

data

Introduction

decision rule

A Testing Procedure

difference in locations

Introduction

difference in proportions

Difference Between Proportions

dependent samples

Difference Between Proportions :

difference of the sample means

Estimation and Confidence Intervals

discrete data

Introduction

discrete random variable

Random Variables

dispersion

The 5 Basic Descriptive

distribution

Describing Discrete Data | Discrete Populations (Probability Models) | Some Probability Examples

double blind study

Difference Between Proportions

effect

Introduction

empirical rule

Empirical Rule | Confidence Intervals for Means

equilikely

More on Probability

error

Relationships Between Variables, Part | Introduction

error of estimation

Introduction

estimate

Describing Discrete Data | Parameters | Normal Quantiles

event

Introduction | Introduction

example

baseball data

Relationships Between Variables, Part | Confidence Intervals for Proportions

battery, two sample

The Wilcoxon | Estimation and Confidence Interval

car battery

Confidence Intervals Based on

church wedding

Observational Studies

concrete

Regression Experimental Designs

elevator

Central Limit Theorem

Etruscan Italian head sizes

Introduction

Etruscan-Italian head sizes

Sample Distributions for Continuous | Measures of Center

Etruscan-Italianhead sizes

Sample Distributions for Continuous

identical twins

Randomized Paired Design

income

Confidence Intervals for Means | Confidence Intervals for Means

jet engine

Independence

ozone

Outliers and Box Plots

Peruvian highlanders

Wilcoxon: Other Alternatives

quail data

Wilcoxon: Other Alternatives | Completely Randomized Designs

spinner

Probabilities | Parameters | More Parameters | Some Probability Examples

suds

Regression Experimental Designs

urn problem

Determination of Probabilities 1: | Random Variables

experiment

Introduction | Introduction

experimental unit

Completely Randomized Designs

experimental units

Regression Experimental Designs

eyeball fit

Relationships Between Variables, Part

first quartile

The 5 Basic Descriptive | Parameters

fit

Relationships Between Variables, Part

fivebasic descriptive statistics

The 5 Basic Descriptive

GIGO

Introduction | Confidence Intervals Based on

hypothesis

Introduction

identical

Relative Frequency

inconclusive results

Estimation and Confidence Interval

increasing

Relationships Between Variables, Part

independent

Relative Frequency

independent events

Independence

infer

Introduction

insignificant

Comparing Data Sets

intercept

Relationships Between Variables, Part

iqr

Parameters

least squares

Relationships Between Variables, Part

location parameter

Parameters

mean

Parameters

median

Parameters

location problem

Comparing Data Sets

lower inner fence

Outliers and Box Plots

LS

Relationships Between Variables, Part

lurking

Observational Studies

maximum

The 5 Basic Descriptive

measure of center

The 5 Basic Descriptive

measures of center

Other Statistics

Q₂

The 5 Basic Descriptive

HL

Measures of Center

Hodges-Lehmann

Measures of Center

mean

Parameters

median

The 5 Basic Descriptive

mode

Sample Distributions for Continuous

sample mean

Measures of Center

sample median

Measures of Center

measures of noise

Other Statistics

measures of relationships

Other Statistics

measures of scale

Other Statistics

interquartile range

The 5 Basic Descriptive | Measures of Scale

IQR

The 5 Basic Descriptive

range

The 5 Basic Descriptive | Measures of Scale | Some Probability Examples

sample standard deviation

Measures of Scale | Normal Quantiles

sample variance

Measures of Scale

variance

More Parameters

median of the differences

Estimation and Confidence Interval

minimum

The 5 Basic Descriptive

model assumption

Relationships Between Variables, Part

model standard deviation

More Parameters

model variance

More Parameters

multiplicative law

Independence

n

Introduction

noise

The 5 Basic Descriptive | Randomized Paired Design

noise parameter

Parameters

noise reducer

Randomized Paired Design

normal

cumulative probability

Normal Distribution

distribution

Normal Distribution | Empirical Rule

percentage point

Normal Quantiles

probability model

Normal Distribution

quantile

Normal Quantiles

quartile

Normal Quantiles

random variable

Normal Distribution

null hypothesis

Introduction

observational study

Observational Studies

observed significance level

The Wilcoxon

one sample Wilcoxon

Signed-Rank Wilcoxon

outlier

The 5 Basic Descriptive | Outliers and Box Plots

p-value

The Wilcoxon

parameter

Parameters | Parameters | Parameters

plots

boxplot

Outliers and Box Plots | Normal Quantiles

comparison boxplots

Comparing Data Sets

comparison dotplots

Sample Distributions for Continuous

dotplot

Sample Distributions for Continuous | Estimation and Confidence Interval

histogram

Sample Distributions for Continuous

residual plot

Relationships Between Variables, Part

scatterplot

Relationships Between Variables, Part

stem leaf

Sample Distributions for Continuous

Poisson

Poisson Probability Model

population

Introduction | Introduction | Introduction

predict

Relationships Between Variables, Part | Relationships Between Variables, Part

probability

Introduction | Probabilities

probability mass function

Discrete Populations (Probability Models)

probability model

Discrete Populations (Probability Models)

question

Introduction | Introduction

random error

Relationships Between Variables, Part | Relationships Between Variables, Part

random number table

Introduction

random sample

Parameters | Introduction

random variable

Random Variables

randomized paired design

Randomized Paired Design

regression

Introduction

regression experimental design

Regression Experimental Designs: A

regression towards the mean

How Regression Got Its

reject

A Testing Procedure

resampling

Introduction

residual

Relationships Between Variables, Part

robust

The 5 Basic Descriptive | Measures of Center | Relationships Between Variables, Part

S

Introduction

sample

Introduction

sample correlation coefficient

Relationships Between Variables, Part

sample covariance

Relationships Between Variables, Part

sample proportion

Describing Discrete Data

sample size

Introduction

sample space

Introduction

sampling with replacement

Independence

scale

The 5 Basic Descriptive

scale parameter

Parameters

interquartile range

Parameters

standard deviation

Parameters

shapes of distributions

Sample Distributions for Continuous

shift

Comparing Data Sets | Introduction

signed-rank Wilcoxon

Signed-Rank Wilcoxon

significant

Comparing Data Sets

skewed

Sample Distributions for Continuous

slope

Relationships Between Variables, Part

SRW

Signed-Rank Wilcoxon

standard error

Confidence Intervals for Means | Regression Experimental Designs

statistic

Describing Discrete Data

symmetric

Sample Distributions for Continuous

symmetry

Normal Quantiles

target parameter

Completely Randomized Designs

test

A Testing Procedure

test statistic

A Testing Procedure

third quartile

The 5 Basic Descriptive

tree diagram

Determination of Probabilities 1: | Some Probability Examples

trial

Introduction | Binomial Probability Model

Type I Error

A Testing Procedure

Type II Error

A Testing Procedure

uniform

Uniform Probability Model

probability model

Uniform Probability Model

unimodal

Sample Distributions for Continuous

upper inner fence

Outliers and Box Plots

Walsh averages

Measures of Center | Signed-Rank Wilcoxon

Wilcoxon

Relationships Between Variables, Part | The Wilcoxon

Wilcoxon fit

Relationships Between Variables, Part

Wilcoxon test statistic

The Wilcoxon

z-score

Normal Distribution