Intro to Experimental Psychology- Exam 2

What are the 6 descriptive Approaches?

1. Case Study

2. Longitudinal Study

3. Cross Sectional (Cohart) Studies

4. Naturalistic Observation

5. Participant Observation

6. Selective Deposit

What is a Case Study?

• Be careful with conclusiveness

• Relatively small data- hopefully get lots of data.

• Helen Keller was a good case study, however we can’t use just her, not enough people.

• Need a lot of data

  • Example: Kids locked in basement, we don’t know circumstances

• Dementia- better results w/ music than talking, however was only 15 peopel, small samples make conclusions difficult. 

Longitudinal Study

• Big Group- track overtime 

  • ex: 1,000 boys interviewed TV habits- Violent TV

• Studies get expensive, can’t ask people to come in long term 

• Time Consuming 

• Morality (Problematic), people drop out due to not seeing results (usually systematic results.) Probably true people dropped out were not seeing results, creates bias.

Cross Sectional Study (Cohart) Studies

• People at different studies 

• IQ score need to know mental age- chronical age

• Talked to diff 6 year olds, 7 year olds, 8 year olds, etc. 

• Careful about drawing that it is developmental. 

DOB DOT-Longitutal Data

• 2025 2030 2035

• 2020. 5 10 15

• 2015 10 15 20

• 2010 15. 20 25

^Coharts  (If all equal; will tell us it’s natural)

Naturalistic Observation

• Watching people from their Natural Habitat

• Charles Darwin

• Lied to his father about medical school

• Observe them in their natural habitat, do not know. 

Hawthorne Effect 

• People act different when they know they are being studied 

• Hidden “observation” 

  • if not hidden influence data.

• No IRB if they don’t know- depends (get it in case study)

Participant Observation

• People putting themselves into psychiactric hospitals

• “Undercover” Policing- join who you want to study.

  • Patient staff interaction

• Run risk of influencing data

• Can be problematic, don’t do it unless you can do it naturally.

Descriptive Statistics 

• Designed to describe 

1. Flat Distribution (draw graph)

2. Normal Distribution 

3. Skewed Distribution 

3 Measures of Central Tendency

1. Mean

2. Median

3. Mode

Mean

Average: Sum of data, X/N, # of scores= X_ (mean)

Median 

50th percentile score, “Mid-Point”, Lowest → highest M

Mode

Most Frequent Score: Mo

2 modes

Bimodal

Measures of Dispersion 

Measures of Spread 

1. Range 

2. Interquartile Range 

3. Variants 

4. Standard Deviation 

Range

(Largest #, Smallest #)

Interquartile Range

IQ1-

IQ2-

IQ3-

Standard Deviation 

Variants square root

For the following data set, assume the mean =25, the standard deviation is 2. Please determine the z-scores and determine what % of the sample falls below that point.

25 26 23

29 20 31

24 25.5 28

Show an example of a positively correlated graph, negative correlated graph, and weak graph (which is the strongest and which is the weakest)

Pearson 

Eugenics- Breed out the lesser population (selective breeding) 

• Thought intelligence is inherited 

• Inheritance and outcome

What is Pearson’s Correlation Coefficient? (Re-check this one)

1. R= +- (0-1)

2. R1=+-.4

3. R2=-.9

4. R3+-.01

Regression

Applied Research (If you know about someone, you can predict the future, i.e Know HS GPA → predict college GPA)

Basic Research vs. Applied Research 

Basic- Collect info, Gain knowledge on stuff 

Applied- can’t do it without basic research 

What is the 5 factor trait theory?

1. Openness to Experience

2. Consciousness

3. Extraversion/ Introversion

4. Agreeableness

5. Neurosim

What are the goals of Science?

1. Describe

2. Predict

3. Explain

4. Control

A causes→B Changes 

IV→ DV

Criteria we must say for this to be true 

1. Necessary- Smoking cigarettes necessary for cancer→ NO!  

2. Sufficient- only factor that is need presence of A always leads to B. 

Independent Variable

Nominal Discrete

Varies and we can measure that

How does Qualitatively vary?

Varies by type

Siblings some vs. none

How does Quantitatively Vary?

Varies by amount

groups/levels 

What does it mean when something is Experimentally Manipulated vs. Predetermined?

Experimentally- I get to decide

Predetermined- (Gender) pre-determined outside our control.

What are the different stats

1. Between Subject Iv’s Split ip genre of music to people- different groups/ people group 1, group2, group 3

2. With-in Subject Iv’s- all genres of music at 3 diff times

   1. group 1, time 1, time2, time

Construct Validity

Are we measuring what we think?

Dependent Variables 

1. Vary 

2. Can be measured 

What are the different ways we can measure time?

1. Duration

2. Latency

3. Accuracy

4. Self-Report

5. Final Ability

Duration

(start) x—————————x (finish)

Get’s Started but stuggles to finish, p

Latency 

—————————x(start) stuggle getting started, push it off

Frequency

How often does something get done?

Ex: Kid making bed/ week

Latency: measure, clock starts when he wakes up, loses points as day goes on

Accuracy

• Politics, do you know how accurate?

• News they listen to

• Test- group that thought they knew a lot did bad

Self-Report 

Ask people about them: What is your mood like? 

Impossible to know people based on behavior 

Accuracy often bad → they often don’t know, need data over time, not in the moment (tricky)

Final Ability

there is a limit to people, not going to get any further.

Don’t care how long, just want to get final performance.

Extraneous variable

?