Chapter 21
Comparing Means
1
In this chapter we will compare two means from two
independent populations. Independent populations have
any impact on each other, for instance: comparing the
height of males and females in a certain company or
comparing the g

Chapter 9 Understanding Randomness
Random: if we know the possible values it can have, but not which particular value it takes
9.1 What is Randomness?
Random: must be fair, nobody can guess outcome before it happens, usually some underlying
set of outcome

Chapter 1 Introduction
Statistics: the science about how to collect, summarize, analyze, present and interpret data and
to make decisions; using data to get knowledge about the world around us (data values useless
without context - five Ws)
Population: en

Chapter 1 Stats Starts Here
1.1 What Is Statistics?
Data: any collection of numbers, characters, images, or other items that provide information
about something
- Vary, helps make sense of world by seeing past underlying variation to find patterns and
rel

Chapter#23 - Chi-Square Tests
Chi-square tests are used when we want to compare several proportions obtained from one or more
categorical variables. For example, we could ask if the birth months of the students in this class
distributed as we would expect

Chapter#7 Linear Regression
7.1 Least Squares The Line of Best Fit
We can model a linear relationship by finding an equation for the straight line that best describes the
pattern of the scatterplot. We then predict the outcome of an individual's response

Chapter 22 Paired Samples
With dependent samples, each subject in one sample has a matched pair in the other sample.
Examples:
Using twins, having one twin in each sample, can reduce certain environmental lurking
variables.
Husband and wives can be matche

Chapter#6 Scatterplots, Association, and Correlation
6.1 Scatterplots
A scatterplot is a display for two quantitative variables. It uses the horizontal axis for the explanatory
variable and the vertical axis for the response variable. The values for the t

Chapter 21 Comparing Two Means
We want to make an inference about the value of 1 2 based on the point estimate y 1 y2 .
To do this, let n1 be the size of sample 1 , n2 be the size of sample 2.
s1 be the standard deviation of sample 1 , s2 be the standard

University of Alberta
Department of Mathematical
and Statistical Sciences
STATS 151- Section A1
Introduction to Applied Statistics I
Midterm Examination
Time: 70 Minutes Instructor: A. Simchi June 1, .2012
INSTRUCTIONS
TEXTBOOK AND SHEET OF NOTES ARE NOT

Lab Assignment 2: Regression and Correlation
By: Sarah McDaniel
ID 1280212
STAT 151, Section E01
M. Kowalski
1a.
b. The relationship between wine consumption and heart disease mortality rate is reasonably
strong because there is a cluster of data within t

Stats Lab 3: Sampling Distributions, Central Limit
Theorem.
By: Sarah McDaniel
ID 1280212
Stats 151 Section E1, M. Kowalski.
November 2nd 2012
1a) The fraction of underfilled water bottles is found to be 0.5, when the
mean is 300, and the standard deviati

STAT 151
INTRODUCTION TO
APPLIED STATISTICS I
MAJID NABIPOOR
CAB 622
nabipoor@ualberta.ca
(Ch.9,10,11)
1
What is statistics?
Many processes in nature (chemical, economical,
agricultural, etc.) follow laws that are not exact, but
are subject to a certain a

Chapter 15
Sampling Distribution
Models
1
The sampling distribution of a statistics is the distribution
of values taken by the statistics in all possible samples of
the same size from a population. Let to have a deeper look
at this by sampling distributio

Chapter 6
Scatterplots, Association,
and Correlations (Relationships)
1
2
Sometimes the purpose of a study is to show that one
variable can explain the outcome of another variable.
Here, instead of studying a single variable, we are
interested in the rela

Chapter 12
From Randomness to
Probability
1
How can , based on a sample of a small percentage of
Canadians, be an accurate estimate of ? After all, a
second sample would give a different value of .
This basic fact is called sampling variability, the value

Chapter 25
Analysis of Variance
1
Hypothesis tests
Proportions
Means
One population
Chapter 17
Chapter 20
Two population
Chapter 19
Chapter 21
The analysis of variance F-test:
When comparing of several populations, the temptation is to
individually test t

Stat 151 Lab 1
1.
In this file there are 1309 cases
Categorical variables: pclass, sex, survived, name
Quantitative variables: age
Identifier variable: name
2.
a)
67.8% of passengers who survived were female and 32.2% of passengers who
survived were male.