Transcript Political Research and Statistics

Univariate Statistics
9/18/2012
Readings
• Chapter 2 Measuring and Describing Variables
(Pollock) (pp.32-33)
• Chapter 2 Descriptive Statistics (Pollock
Workbook)
• Homework: Chapter 1 Introduction to SPSS
(Pollock Workbook)
– Question 1 Parts A &B
– Question 2
About the Homework
• It must be turned in
during class.
• It cannot be emailed
• It must appear on the
workbook paper
(original or a
photocopy)
• You cannot:
OPPORTUNITIES TO DISCUSS
COURSE CONTENT
Office Hours For the Week
• When
– Weds and Fri 11-1
– Thursday 8-12
– And appointment
Course Learning Objectives
• Students will learn the research methods
commonly used in behavioral sciences and will
be able to interpret and explain empirical
data.
• Students will achieve competency in
conducting statistical data analysis using the
SPSS software program.
Variables
Variables
• Measured Concepts
• We need to operationalize concepts to test
hypotheses
Four Categories of Variables
Categorical
Nominal
• Name
Ordinal
• Name
• Provide value
• And provide value
• And Order
CONTINUOUS VARIABLES
What about them
• The values matter
• Your variable includes all possible values, not
just the one’s that you assign.
• Name, order, and the distances between
values matter.
Interval Level Variables
• The values matter at
this level
• The distances matter
• The zero is arbitrary
Examples of Interval Scales
Ratio Variables
• The Full properties of
numbers
• A zero means the
absence of a property
• Classify, order, set units
of distance
Examples
Lets Look at this one again
DESCRIPTIVE STATISTICS
Descriptive Statistics
• These simply describe the attributes of a
single variable.
• You cannot test here (you need two variables)
• Why do them?
Categories of Descriptive Statistics
Measures of Central Tendency
• The most common, the
middle, the average
Measures of Dispersion
• How wide is our range of
data, how close to the
middle are the values
distributed
• Mean, Median and Mode
• Range, Variance, Standard
Deviation
Frequency Distributions
• This Provides counts and percentages (relative
frequencies) of the values for a given variable
• Computing a relative Frequency
• The Cumulative Percent is percentage of
observations less than or equal to the category
Examples
• St. Edward’s Data
The Mode
• the most frequent
observation of the
variable in a distribution
• Which category is most
common
• There can be more than
1
Examples
• What are the Modes here?
1. 110,105.100.100.100.100.99.98
2. 110.105.105.105.100.95.95.95.90
Advantages and Disadvantages
• Advantages of the
Mode
• Disadvantages of the
Mode
Where Parties Should Go in A Normal
Distribution
They Move To the Center, why?
What About A Bimodal Distribution?
Party Polarization
A polymodal System
THE MEDIAN
The Median
• It only tells us one thing
• the value that lies in the
middle of the data
when arranged in
ascending order.
Examples
• The University of Texas
• The 78704 Zip Code
Examples
• The middle observation = (N+1)/2
• Characteristics and problems of the median
• Three Examples
– (133,113,112,95,94)
– (27,12,78,104,45,34)
– (105,102,101,92,91,80)
Locating the Median
Finding the Median
• location of median case (1747+1)/2 = 874
• Where Does that case fall?
– Case 1 through 534 = has value of 0
– Case 535 through 1747 = has value of 1
• Case 874 is more than 535 and less than 1747
• THE MEDIAN IS 1, the category is voted
You can also
look here for
where 50%
falls
Lets Try Again
Median Voter Theory
THE MEAN
The Mean
• What is it
• How do you compute
it?
About the Mean
• Characteristics of the Mean
• Problems of the Mean
An Example
Name
Income
Skipper
50.00
Gilligan
150.00
Mary Ann
150.00
Professor
400.00
Mrs. Howell
500.00
Mr. Howell
1000.00
Ginger
3000.00
Picking the Right Measure
Measure
Level of Analysis
Mode
Nominal, Ordinal, Ratio, Interval
Median
Ordinal, Ratio, Interval
Mean
Ratio, interval (sometimes ordinal)