Chapter 2Looking at data - Relationships
ExaminingRelationships
Most statistical studies involve more than one variable.
This chapter is about graphical and numerical methods for describing
relationships between variables.
AssociationbetweenVariables
Two
Stat 1561 Barnhart Topics List for 1st Exam
Definition of statistics
Population vs. unit (individual)
Random vs. biased
Sample vs. Population
Statistic vs. Parameter
Descriptive vs. Inferential
Qualitative (Categorical) vs. Quantitative Data
Frequencies,
STAT 1561
Exam 1 Review
Spring 2014
The exam will begin with a problem of objective questions about the concepts that we have
studied. These questions could be True or False questions, multiple choice questions, fill in the
blank questions or short answer
1.2 Describing Distributions with Numbers
Describing Distributions
A description of a distribution should include its shape and numbers describing its
center and spread.
To interpret measures of center and spread and to choose among the several
measures w
Tests of Significance
Also called Hypothesis Tests
Definition
A test of significance is a procedure used to
assess the evidence provided by data about
some claim concerning a population
parameter.
Concept
An outcome that would rarely happen if a
claim wer
Chapter 7: Inference for Distributions
Section 7.1: Inference for the Mean of a Population
When the sampling distribution of
involving
by standardizing:
is close to Normal, we can find probabilities
When we dont know , we can estimate it using the sample
Section 7.2: Comparing Two Means
Two-Sample Problems
What if we want to compare the mean of some quantitative variable for the
individuals in two populations, Population 1 and Population 2?
Our parameters of interest are the population means 1 and 2.
The
Chapter 1: Looking at Data -Distributions
Attributes of Data Sets
Cases (Units, Subjects)- the objects described by the data
Labels - used to identify the objects
Variables characteristics of the objects
Values
Examples
Cases - Students in my Stat 1561 cl
STAT 1561
Exam 2 Review
Spring 2014
The exam will include a list of multiple choice questions and a list of true or false
questions about the concepts that we have studied. Most (but not all) of these questions relate to
the material from Chapter 3. On th
STAT 1561
Exam 3 Review
Spring 2014
The first problem is a list of multiple choice questions about the concepts that we have studied in
chapters 5 and 6. On this exam these questions constitute about 20 % of the exam. To prepare for these
questions you sh
STAT 1561
FINAL EXAM
REVIEW SHEET
The Final Exam is scheduled for:
Friday, May 9 from 9:15 to 11:15 am for the 10:00 am class
and
Friday, May 9 from 11:45 am to 1:45 pm for the 1:00 pm class.
Both will be in our regular classroom (MT 210).
I will have off
4.5 Probability Rules
Our study of probability has concentrated on random variables and their
distributions. Now we return to the laws that govern any assignment of
probabilities.
Probability Rules
Rule 1: The probability P(A) of any event A satisfies 0 P
4.4 Means and Variances of Random Variables
The Mean of a Random Variable
When analyzing discrete random variables, well follow the same strategy we
used with quantitative datadescribe the shape, center, and spread, and identify
any outliers.
The mean of
Chapter 4Probability The Study of Randomness
4.1 Randomness
Two Definitions of Random
Lacking a definite plan, purpose or pattern, haphazard
Consisting of or relating to a set of elements that have a definite
probability of occurring with a specific frequ
Chapter 6: Introduction to Inference
Types of Inferences
We will consider two types of inferences:
Confidence Intervals (section 6.1)
Tests of Significance (section 6.2)
Both types are based upon the sampling distribution of statistics so they involve
pro
Chapter 5: Sampling Distributions
Parameters and Statistics
A parameter is a number that describes some characteristic of the population. In
statistical practice, the value of a parameter is not known because we
cannot examine the entire population.
A sta
3.2 Sampling Design
Population and Sample
The population in a statistical study is the entire group of individuals about which
we want information.
A sample is the part of the population from which we actually collect information.
We use information from
5.2 : Sampling Distributions for Counts and Proportions
Counts and proportions are discrete statistics that describe categorical data.
When there are only two outcomes for an RV we summarize the results by giving
the count of one of the possible outcomes.
Stat 1561 topics list 2nd test
3 types of probability
Independent and dependent events
Sample spaces and events
Mutually exclusive events
Complement of an event
Probability distributions
Conditional probability
Addition and multiplication rules for probab