1. Concept : Innocent until proven guilty (on the basis of gathered information)
Hypothesis Testing is making a conclusion about the validity (truth) of a yes
or no question. Therefore you are in danger of making two potential errors.
Introduction and terminology:
To study relationships between variables, we must measure both (or more)
variables on the same individual.
Response variable the outcome of the study, that is the variable you are
interested in draw
Experiments, Counting Rules, Probability
- a numerical measure of the likelihood (chance) that an event will occur.
Experiment A process that generates well-defined outcomes
Outcome a well-defined response from a sin
3.5 Measures of Association between two variables:
is a measure of linear association between two numerical variables
B. Correlation Coefficient:
is a measure of strength and direction of a linear association between two numerical
Chapter 2 Tabular and Graphical Presentations
2.1-2.3 Summarizing a single variable
Examining Data: Exploratory Data Analysis
Two basic strategies:
1) Examine each variable by itself, then move to relationships
2) Begin with picture
Discrete Probability Distributions
1. a random variable, X, is a numerical description of an outcome of a experiment.
a. A discrete random variable is a finite or countable finite number of values (outcomes)
b. A continuous random v
Descriptive Statistics: Numerical Summary Measures
3.1 Describing Numerical data distributions:
A. Measures of Location:
Calculating the Center of the distribution, Measures of Central Tendency (location) :
1. Mean arithmetic average
The Normal Distribution
Omit 6.1 and 6.3
A Density Curve is a curve that
- is always on or above the horizontal axis, meaning f(x) is nonnegative
- the total area under the curve representing the graph of f(x) equals 1.
A density curve describe
The Binomial Distribution
A. The Properties of a Binomial Experiment:
1. The experiment consists of n identical trials (SRS of size n)
2. Two outcomes are possible on each trial. We will refer to one outcome as a
success and the other a failure.
3. The pr
Sampling and Sampling Distributions
reliable sample information (design, SRS)
data summaries (descriptive statistics)
Z tables for estimating p
t tables for estimating )
estimates (best guess) +/- er