Title: Statistics and the Research Process
 1Statistics and the Research Process
  2Scientific Research
- The goal of science is to understand the 
____________________  - We examine a specific _________ on a specific 
___________ in a specific ___________  - Then, we ____________ back to the broader 
behaviors and laws with which we began. 
  3Review
- The entire group to which a law applies is the 
___________________  - A _____________ is a relatively small subset of a 
population that is intended to represent, or 
stand for, the population  - The individuals measured in a sample are called 
the _____________________________ 
  4Drawing Inferences
- We use the scores in a sample to _____________or 
to estimate the scores we would expect to find in 
the population. 
  5Representativeness
- In a ________________ sample, the characteristics 
of the ________________accurately reflect the 
characteristics of the __________________. 
  6Random Sampling
- Random sampling is a method of selecting a sample 
in which the individuals are _____________________
________ from the population. 
  7Unrepresentative Samples
- A random sample should be representative of the 
population, but never automatically assume that a 
sample is representative of the population. 
  8Examining Relationships
- A __________________ occurs when a change in one 
variable is accompanied by a _________________ in 
another variable. 
  9Strength of a Relationship
- The strength of a relationship is the extent to 
which one value of Y is ____________________ with 
one and only one value of X. 
  10Factors Affecting Strength
- A _______________ relationship may be due to 
additional extraneous influences and/or 
individual differences  - _________________________ refer to the fact that 
no two individuals are identical 
  11Graphing Relationships
- Describe a relationship using the general format 
 - Scores on the Y variable change as a function of 
changes in the X variable.  - The given variable in a study is the X variable.
 
  12Four Sample Graphs
- A graph showing 
 - a perfectly 
 - consistent 
 - association.
 
  13Four Sample Graphs
- A relationship 
 - that is not 
 - perfectly 
 - consistent.
 
  14Four Sample Graphs
  15Four Sample Graphs
  16Measurement Scales 
 17Characteristics of Variables
- Two important characteristics of variables are 
 - The __________________________ scale involved 
 - Whether it is continuous or discrete
 
  18Measurement Scales
- 4 types of measurement scales 
 - _______________ 
 - _________________ 
 - __________________ 
 - ___________________ 
 - Differ in mathematical properties
 
  19Nominal Scales
- ___________________ level of measurement 
 - Used with _______________ rather than 
___________________ data  - Examples 
 - Gender, types of music, ethnicity, eye color 
 
  20Nominal Scales
- Variable is divided into categories 
 - Measured by determining which _____________person 
belongs to  - Classification 
 - Equivalence
 
  21Example
- Interested in type of music people enjoy. Ask 
people to choose favorite type of music. You 
find that  - 15 like Rock 
 - 20 like Pop 
 - 12 like Country 
 - 10 like RB
 
  22Ordinal Scale
- Next higher level of measurement 
 - ________________ depending on whether they 
possess more, less, or the same amount of the 
measured variable  - Is A gt B, B gt A, or A  B?
 
  23Examples of Ordinal Scale
- Rankings of contestants in a race 
 - Participant 1 came in first place 
 - Participant 2 came in second place 
 - Participant 3 came in third place 
 - Does not tell us about the _______________________
_________ 
  24Interval Scales
- Higher level than ordinal 
 - Possesses properties of ________________ and 
equal intervals b/w adjacent units  - Does not have an _____________________ point
 
  25Interval
- Example 
 - Temperature 
 - Equal amounts of heat b/w each unit 
 - No absolute zero point
 
  26Ratio
- ___________________level of measurement 
 - Same properties of the interval scale but also 
has an ___________________ point  - Examples 
 - Weight, height, age 
 
  27Figure 2.1 
 28Summary of Measurement Scales 
 29Inspecting data 
 30Inspection
- Before analyzing the data in any way, you should 
look at the data.  - Why might this be a good first step to take?
 
  31How do we inspect our data?
- Order data in terms of magnitude 
 - From highest to lowest 
 - Or from lowest to highest 
 
  32Numerical Stroop Data
- There were 28 trials (questions) 
 - Response time (RT) for each is in seconds and 
tenths of seconds  - 3.5 means it took me 3.5 seconds to respond
 
  33Look for Klinkers or Outliers
- Are the numbers out of range? 
 - If the top possible response is 7, 8 would be an 
invalid (purple)  - Did some responses take much too long? (yellow?) 
 - Were some responses very short? (blue?) 
 
  34Which Responses Will You Use?
- For Reaction Time (RT), we often use only correct 
responses  - It is not clear what processes were occurring 
with errors  - Delete errors from the RT data
 
  35Score the Data
- Count the numbers condition 
 - Correct responses in Correct 
 - Put 1 if my Response matches Correct 
 - Otherwise, answer wrong (0)
 
  36Stem and Leaf Plots (Displays)
- Decide what number to use as your stem 
 - It depends on how many digits 
 - If there are 2 digits (e.g., 15, 35), you 
probably will use the tens as the stem and the 
ones as the leaf  - If there are three digits (e.g., 126, 138), you 
probably will use the first two as the stem and 
the third as the leaf 
  37RT Data in Seconds
- 3.5 sec. 
 - 6.8 sec. 
 - 0.9 sec 
 - 1.6 sec 
 - Use the number of seconds as the stem and tenths 
of a second as the leaf 
  38Order your data from fastest to slowest
- Remove Errors 
 - Drop those fast times because they were errors
 
  39Creating a Stem and Leaf Plot 
 40What Can We Learn from Stem and Leaf Plots?
- Look at the distribution 
 - Are most of the numbers very low with only a few 
high ones?  - With reaction time (RT) data, this is what you 
get  - Its called positively skewed because there are 
relatively few large scores  - Later well learn whether this is a problem 
 
  41(No Transcript) 
 42What Can We Learn from Stem and Leaf Plots?
- Are there potential outliers 
 - The 11 looks much larger than the other scores 
 - Later well learn what to do about this