CHAPTER 2 / Research Methods
Steps in the Scientific Method
 Define a researchable problem
 Review the literature
 Formulate a hypothesis
 Select an appropriate method and design the project
 Collect data
 Analyze the data and state the results
 Draw relevant conclusions and interpret results [and publish findings]
Methods of Data Collection
 Case Studies
 Observation
 Survey Methods
 Correlational Research
 ==================
 Formal Experiments
Case Studies
 Used to provide an in-depth analysis of a person or small group
 Typically performed on persons with exceptional life experiences or abilities (both positive and
negative)
 Limitation: results cannot be generalized to other similar cases
Observation
 Perhaps the most fundamental research method of all – observing behavior
 Used to study directly observable behavior (not for studying beliefs)
 Doing observation well requires objectivity
 Operational definitions are helpful
 All Observation May Be Either…
 Naturalistic or Laboratory
 Unobtrusive or Obtrusive
 Non-participant or Participant
…or any combination of the above
Survey Methods
 Used to assess attitudes, opinions, beliefs and perceptions not accessible to direct observation
 May also be used as a self-report method of studying frequency of behavior
 Two Forms of Surveys
 Questionnaires:
 Advantages: anonymous and efficient
 Disadvantage: response rate
 Interviews:
 Advantages: more detailed & personal, response rate
 Disadvantages: time & labor intensive, socially desirable responses
Survey Sampling
 Population: the target group for the survey (Collin students ages of 18 – 24 who work fulltime)
 Sample: subjects selected from the population as participants in the survey
 Random Sample: where each person in the population has an equal chance of being chosen as a part
of the sample
 Only surveys utilizing true random sampling produce results which may be generalized
Correlational Research vs. True Experimental Method
 Both are used to examine the relationship between variables
 Variable: a factor who’s numerical value can change (age, height, race, education, income,
intelligence, self-esteem, memory recall)
 In most cases, a formal experiment is best method
 HOWEVER, certain variable are not appropriate for experimental research
Variables Not Appropriate for True Experimental Research
 Cigarette smoking & lung cancer
 Single parent families & self-esteem of the child
 Therefore, correlational research may be in order when the variables:
– Cannot be ethically manipulated
– Cannot be controlled or manipulated
Correlational Research
 Used to examine the relationship between variables as they occur naturally
 NO manipulation of variables is attempted
 Correlational research can determine
– [1] IF there is a relationship,
– [2] strength of the relationship and
– [3] type of relationship, HOWEVER…
 NO CAUSE AND EFFECT RELATIONSHIP CAN BE DETERMINED using a correlational strategy (the major
limitation)
 The Problem with Correlational Research
Correlation is Not Causation Example
 ‘Hyper-Texting Associated with Health Risks for Teens’
– Case Western Reserve University School of Medicine
– HS students from urban Midwestern area
– 20% = ‘hyper-texters’ [120+ messages/ school day]
– Many = female, lower SES, minority, no father at home
– ‘Hyper-texters’ reported to be:
 40% more likely to smoke
 x2 more likely to use alcohol
 43% more likely to binge drink
 41% more likely to use drugs
 55% more likely to engage in fights
 3.5% more likely to have had sex
 90% more likely to have had 4+ sexual partners
– Faulty Conclusions From the Study:
 “The startling results of this study suggest that when left unchecked, texting and
other widely popular methods of staying connected can have dangerous effects on
teenagers.”
 “This should be a wake-up call for parents to not only help their children stay safe by
not texting and driving, but by discouraging excessive use of the cell phone or social
websites in general.”
Correlation Coefficient
 A number derived from a statistical formula that indicates two things about the relationship between
variables:
– The strength of the relationship
– The type of relationship
 Coefficients are numbers between –1.0 and +1.0 on a number line
Correlation Coefficients
 Examples: -.27 +.15 +.48 -.89
Strength of a Correlation Coefficient
 Numbers closer to either a +1.0 or a –1.0 indicate a stronger relationship
 Numbers closer to zero indicate a weaker relationship
 A coefficient of zero indicates NO relationship
 Simply put, the larger the number, the stronger the relationship, regardless of the + or – sign in front
of it
 ‘POP QUIZ’
Which of the following indicates the strongest relationship between variables?
A. -.58
B. +.13
C. +.85
D. -.33
E. -.95
Which of the following indicates the weakest relationship between variables?
A. -.58
B. +.13
C. +.85
D. -.33
E. -.95
Type of Relationship Indicated by a Correlation Coefficient
 Positive Correlation: when two variables tend to increase together
 Positive Correlation: ˄˄ or ˅˅
 Negative Correlation: when variable are seen in and inverse relationship
 Negative Correlation: ˄˅ or ˅˄
REVIEW: The Descriptive Methods
 Case studies, observation, surveys, correlational research
 All involve NO MANIPULATION of the variables
 Variables are simply observed but no direct attempt to cause a change is made
 Cannot be used to determine a cause and effect relationship
Formal Experiments / The Experimental Method
 Overall, the most powerful and accurate research method
 Used to examine the relationship between variables in a controlled environment (unlike
correlational)
 Direct manipulation of variables takes place
 When done well, and statistically significant results achieved, experiments CAN determine a cause
and effect relationship
The Groups
 Experimental Group: group that receives the variable being tested
 Control Group: group that doesn’t get the variable being tested
 Control group is used for comparison in order to see what change has resulted from the test variable
 Goal: to keep everything the same between groups except the test (independent) variable
The Variables
 Independent Variable: variable we suspect will cause a change in the other
 Dependent Variable: variable we suspect will be changed or affected by the independent variable
Hypothetical Experiment (Classroom Example)
 Hypothesis: a blood alcohol level of 0.1 will significantly negatively affect ability to accurately drive a
car
 Variables: driving and alcohol
 Independent variable?
 Dependent variable?
Selection of Subjects
 Goal: to examine the pure effects of alcohol on driving
 Possible Subject Groups:
– Social drinkers?
– Non-drinkers?***
– “Experienced” drinkers?
 Non-drinkers: perhaps the best choice
Ethical Considerations
 Informed Consent
 Must tell subjects enough about the experiment to make an informed decision on whether to
participate
 Subjects will be told “you may or may not be put in a group that gets drunk and drives a car”
Assigning Subjects to Groups
 Subjects will be RANDOMLY assigned to groups
 Random assignment to groups will minimize or eliminate difference between the two groups
 Important: Subjects are NOT told the group to which they’ve been assigned
– Why? [Single Blind: don’t want to tip off subjects as to what group they’re in]
Placebo Effect
 Placebo Effect: when the expectation of the subjects affect the outcome more so than the variables
being studied
 Controlling for the placebo effect involves the use of a placebo
 Placebo: a fake or false variable similar in appearance to the independent variable
 Example of Placebo Effect
Experimental Group (Alcohol & OJ)
Poor Driving Ability
Control Group #1 (OJ only)
Poor Driving Ability
Control Group #2 (nothing)
Good Driving Ability
 NO Placebo Effect Occurs
Experimental Group (Alcohol & OJ)
Poor Driving Ability
Control Group #1 (OJ only)
Good Driving Ability
Control Group #2 (nothing)
Good Driving Ability
Administering the Independent Variable
 How could we be sure each subject in the experimental group is of the same level of intoxication?
– Check blood alcohol level with a breathing test
 If the experimental subjects blow into the detector, the control subjects must also
Double-Blind Method
 Double Blind Method = when neither the subjects nor experimenters know which group received the
actual independent variable
 Used to reduce experimenter bias
 Important when rating/ranking of the dependent variable is subjective (easily affected by human
biases)
Variables to Hold Constant
 The only difference between the experimental and control groups should be the alcohol
 All other variables should be held constant between the groups
 Examples of variables to control?
– Experimenter should use the same car, same road course, same time of day the subjects
drive the course, same weather conditions, same food before driving, same minimum driving
speed for all subjects…