1. Reasoning in Psychology Using Statistics
Spring 2019

2. What are Statistics? “It’s about almost everything in modern society.”
Bennett, Briggs, Triola (2003), Statistical Reasoning for Everyday life
Statistics: tools used to make Data based decisions
Data: numbers with a context
Examples of stocks, sports, weather
What are Statistics?

3. Video to Course Main points from the video
Context
Main points from the video
Every statistical test starts with an appropriate selection of subjects
Inferences must be based on more than one observation because of variability
Two types of error must be controlled while testing hypotheses
A decision is based on two things:
The difference between groups
The variability of the scores
Week 3
Descriptive
Statistics
Weeks 5&6
Week 10
Weeks 10-15
Examples of stocks, sports, weather
Inferential
Statistics
Video to Course

4. What are all these numbers?
Data: numbers with a context
e.g., How were numbers measured? Who did they come from? What do they mean?
Understanding the context in which the observations are made is critical for both doing statistical analyses as well as interpreting the results.
Examples of stocks, sports, weather
What are all these numbers?

5. “The world of statistics starts with a question, not with data”
Keller 2006, Tao of Statistics
Traditional Knowing: truth or error
Assumes perfect uniformity
Assumes error-free repetitions
Modern Knowing: probabilistic
Assumes variability
Our focus: Scientific Method
Systematic observation (& experimentation) used to explain how and why events occur
Systematic observations constitute data
Statistics are used to describe data & relationships within data
T r u
T r u t h
Ways of Knowing
“Alternative facts”
“Truthiness”

6. “The world of statistics starts with a question, not with data”
Keller 2006, Tao of Statistics
Scientific Method
Ask research question
Identify variables and formulate hypotheses
Define population
Select research methodology
Collect data from sample
Analyze data
Draw conclusions based on data
Repeat
Statistics
A process
The research process

7. An Example Claim: Absence makes the heart grow fonder
But, what about your observation that long distance romances never work out? (Out of sight, out of mind) ??
How to test the claim scientifically?
What data do we collect?
Who to test?
How do we make our observations?
An Example
Actual examples:
Jiang & Hancock (2013)

8. Variables What data do we collect? Identify what we are studying
Characteristics or conditions that change or have different values for different individuals (or situations)
Independent (explanatory) variables (IV)
Variable that has causal impact
In experiment, variable that is manipulated by researcher
Dependent (response) variable (DV)
Variable observed for changes to assess effect of the manipulation (of the IV) in an experiment
Variables measured in observational research
Variables
Actual example:
Jiang & Hancock (2013)

9. Brief tour of SPSS To switch between the Two view windows: views click
on the tabs
Two view windows:
Brief tour of SPSS

10. This is where you specify the details about the variables
Each row corresponds to a variable
Each column corresponds to a feature of the variables
The Variable View

11. The Data View Each row corresponds to an experimental unit
(called “cases” in SPSS lingo)
Each column corresponds to a variable
So each column in the data view corresponds to a row in the
variable view
The Data View

12. Independent and Dependent Variables
Absence makes the heart grow fonder
What are some potential Independent (explanatory) variables?
How long apart?
How far apart?
How much communication?
How “strong” was the relationship to begin with (quasi-independent)?
What are some potential Dependent (response) variables?
Ratings of fondness for partner
Heart rate when seeing a picture of partner
fMRI of brain when hearing partner’s voice ??
Independent and Dependent Variables
Actual example:
Jiang & Hancock (2013)

13. What is the level at which the research is focused
What is the level at which the research is focused? (what do the rows in the Data view correspond to?)
Individuals
Between individuals
Within individuals
Across groups
Couples
Families
Cities
Ethnic groups
Our example: Absence makes the heart grow fonder
What level(s) could we focus on?
Experimental Unit
Actual example:
Jiang & Hancock (2013)

14. Observing participants (getting data)
What data do we collect?
Who to test?
Population
Set of all individuals of interest
Typically no access to whole population
Sample
Subset of population data collected from
Inferential Statistics: Test sample & generalize results to population as a whole
Observing participants (getting data)
Actual example:
Jiang & Hancock (2013)

15. Basic Research Methods
Absence makes the heart grow fonder
How could we go about testing this?
What data should we collect?
Who to test?
How should we make our observations?
Observational study (Explanatory and Response variables)
Observe & measure variables of interest to find relationships
No attempt to manipulate or influence responses
Experimental methodology (Independent and Dependent variables)
Independent variable manipulated while changes observed in another variable (dependent)
Can establish cause-and-effect relationships
Extensive controls to minimize extraneous sources of variability
Quasi-Experimental methodology
One (or more) of the independent variables is a pre-existing characteristic (e.g., sex, age, etc.)
Basic Research Methods
Actual example:
Jiang & Hancock (2013)

16. Today’s Lab Learning the basics of SPSS including entering data
Reminder: Monday is MLK Day, so no class or labs