Jargon

1
Jargon Basic Concepts

• Howell
• Statistical Methods for Psychology

2
Questions

• Define and illustrate
• Population, Sample
• Parameter, Statistic
• Descriptive, inferential statistics
• Random selection (sampling), assignment
• Internal, External validity
• Discrete, continuous variables
• Scale types (nominal, ordinal, interval, ratio)

3
Population vs. Sample

• Population collection of all the objects of
  interest to researcher (you).
• College students, students at USF
• Sample subset of objects from the population
• Want a representative sample
• Samples are relatively practical
• Random samples have good properties
• One persons sample is anothers population

4
Parameter vs. Statistic

• Parameter numerical summary of population
• E.g., mean, standard deviation
• Statistic numerical summary of sample
• E.g., mean, standard deviation
• Typically we compute statistics and estimate
  parameters using statistics.

5
Descriptive vs. Inferential

• Descriptive statistics describe a sample
• How tall are these students?
• Inferential statistics use sample statistics to
  make decisions about populations.
• Is one method of instruction better than another?

6
Random Select Assign

• Random selection is a process of picking a sample
  from a population so that each element has the
  same probability of being sampled.
• E.g., lottery, every 3rd name from a list (this
  is actually a systematic sample but its good)
• Random assignment is assignment to treatment so
  that each element has an equal probability of
  being assigned to each treatment.
• E.g., lottery, every other name, etc.
• Both are typically accomplished by lists (aka
  frames) and computer generated numbers (e.g., SAS
  PROC PLAN)

7
Internal, External Validity

• Internal validity - quality of inferences about
  the study itself. Random assignment, history,
  maturation, etc.
• External validity quality of inferences from
  the study to the larger domain of interest.
  Representative sample of participants, task
  relevance, behavioral consequents, etc. Aka
  generalizability of the results (but not
  generalizability study).

8
Variable Distribution

• Variable vs. constant
• Attribute either varies across objects or not
• Distribution Collection of data
• Distribution Array of scores
• Height
• Beck Depression Index
• Rat bar press
• Wonderlic

9
Discrete vs. Continuous

• Math
• Integer vs. real numbers
• Data
• Categorical vs. continuous (many valued, ordered)
• Examples
• Political party, job satisfaction, response time,
  country of origin

10
Scale types

• Nominal, ordinal, interval, ratio
• Nominal categories. No ordering mean has no
  connection to attributes
• Ordinal rank order only
• Interval rank order plus equal interval. ratio
  of differences has meaning
• Ratio rank order, equal intervals, rational
  zero point. Ratio of numbers has meaning.

11
Scale Types Footrace review
Nominal Ordinal Interval Ratio
ID number Rank order of finish Time of day of finish Elapsed time from start
043 1 1057 a.m. 4 min
011 2 10.59 a.m. 6 min
136 3 1101 a.m. 8 min
112 4 1102 a.m. 9 min
086 5 1104 a.m. 11 min
12
Review
Find a partner to work on this exercise. Suppose
you want to know whether one brand of tennis shoe
is better than another. You have about 10K from
a grant to study this. Describe a study you might
conduct to find out. What might be your
population, sample, independent and dependent
variables? What statistics might you want to
compute? Never mind the actual statistical test
at this point. What data would you gather? What
might a critic say about the internal and
external validity of your study? What scale
types are your IV and DV?