I.
II.
7.1 Hypothesis Testing: The Randomization Test
1. how different do two samples have to be in order for us to infer that the populations that
generated them are actually different
2. one way to test this is to compare two sample means and to see how

Chapter 5: Sampling Distributions
I.
5.1 Basic Ideas
A. Sampling Variability
1. sampling variability - variability among random samples from the same
population
2. sampling distribution - a probability distribution that characterizes some
aspect of sampli

Chapter 2
I.
2.1 Introduction
A. Variables
1. variable - is a characteristic of a person or a thing that can be assigned a
number or a category
2. categorical variable - is a variable that records which of several categories
a person or thing is in. EX: b

CH 4 The Normal Distribution
I.
4.1 Introduction
1. normal curve - is a symmetric bell-shaped curve
2. normal distribution - a distribution represented by a normal curve
3. nor curve can describe the distribution of an observed variable Y in two
ways
a) a

I.
II.
10.1 Introduction
1. contingency tables - the dependence or association between the column
variable and the row variable
2. each category in the contingency table is called a cell; a 2 X 2 table has
four cells
10.2 The Chi-Square Test for the 2 X 2

Chapter 6: Confidence Intervals
I.
6.1 Statistical Estimation
A.
II.
6.2 Standard Error of the Mean
A. Standard error versus Standard Deviation
1. SD describes the dispersion of the data
2. SE describes the unreliability in the mean of the sample
3. as n