RMTD 404
Lecture 8
Power
Recall what you learned about statistical errors in Chapter 4:
Type I Error: Finding a difference when there is no true difference in the
populations (i.e., incorrectly rejecting a true null hypothesis), designated by .
Type II

RMTD 404
Lecture 4
Chi Squares
In Chapter 1, you learned to differentiate between quantitative
(aka measurement or numerical) and (aka frequency or
categorical) qualitative variables. Most of this course will focus on
statistical procedures that can be ap

RMTD 404
Lecture 9
Correlation & Regression
In two independent samples t-test, differences between the means of
independent variable groups on the dependent variable is a measure of
associationif the group means differ, then there is a relationship betwee

RMTD 404
Lecture 5
Measures of Association for
Categorical Data
One problem with the hypothesis testing framework that well discuss
later is the fact that any observed difference has the potential to
be statistically significant, provided the sample size

RMTD 404
Lecture 3
Distributions and Probability
From this point on, we are going to work extensively with
distributions and probabilities of events.
Just about every situation that we deal with in statistics involves
estimating probabilities of events

RMTD 404
Lecture 6
Dog Colors
Observed
Judge 1
Judge 2
Green
Green
Expected
Judge 1
Red
Blue
Total
10
1
3
14
Red
2
5
2
9
Blue
0
1
9
12
7
14
Judge 2
Total
Sum
(Agree)
24
k
Red
Blue
Total
5.090909
1
3
14
Red
2
1.909091
2
9
10
Blue
0
1
4.242424
10
33
Total
1

RMTD 404
Lecture 2
Summation Notation
We need a way to talk about the processes that occur in a
statistical analysis in a succinct way
We use summation notation
- stands for sum
X - stands for the variable we sum
i - referred to as a subscripting index

RMTD 404
Lecture 7
Two Independent Samples t Test
Probably the most common experimental design involving two groups is one in
which participants are random assigned into treatment and control
conditions.
Because such observations are likely to have minima