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PSYCHOL 1000 > Chapter 2 > Flashcards

Chapter 2 Flashcards

1
Q

Steps in the Scientific Process

A
  1. Initial observation/question (i.e. friend drank a lot and has bad hand-eye coordination)
  2. Form hypothesis (i.e. if the alcohol consumption increases, then hand-eye coordination decreases)
  3. Test hypothesis (i.e. conducting research; in a lab divide individuals into 2 groups randomly, one group consumes 2 bottles of beer and the other does not, then test hand-eye coordination by catching ball)
  4. Analyze data (do results support the hypothesis? i.e. did we find alcohol increases or decreases hand-eye coordination)
  5. Further research and theory building (adjust theory on the basis of new findings; if data/results supports the theory, there is no need for adjustments)
  6. New hypothesis derived from theory
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2
Q

Hindsight Understanding

A

Arrive at explanations after-the-fact.

- Major limitation is due to various explanations for behaviour with no sure way to determine correct alternative.

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3
Q

Science

A

An approach to asking and answering questions
* Peer-reviewed
- before any research publication in scientific journal, must be reviewed by other psychologists to ensure quality and accuracy
* Maintain rigorous standards for honesty and accuracy
* Reproducible results demanded
- enough details in methodology section for others to reproduce the study
* Failures are searched for and studied
- learn from mistakes
*more is learned overtime about processes under study
convinced by evidence or logical reasoning

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4
Q

Pseudoscience

A
  • Not peer-reviewed
  • No rigorous standards for honesty and accuracy
  • Results cannot be produced or verified
  • Failures are ignored, excused or hidden
  • Overtime very little is learned
  • convinced by faith or belief
    i. e. palm reading, fortune telling, astrology
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5
Q

Theories

A

Formal statements that explain how and why certain events are related (broader than hypotheses)

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6
Q

Hypothesis

A

Tentative explanations or predictions that must be testable (takes the form of “if…then…” statement; i.e. “if I I’m tired then I need to sleep” but more scientific)

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7
Q

Variable

A

factors that you want to explore (i.e. hand-eye coordination, age, gender)

  • Operational variable defines a variable in terms of the specific procedure used to produce or measure it
  • translate an abstract concept into something observable and measurable
  • how you are specifically going to define your variable
  • i.e. study aggression → you would measure it by number of punches or number of verbal threats
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8
Q

A Good Theory…

A
  • Incorporates existing facts/observations within a single framework (easily understandable)
  • Are testable (Freud’s theories are often criticized because not testable)
  • Supported by new research findings
  • Are parsimonious (simple as possible; Law of Parsimony: two theories can explain and predict same phenomena equally well, simpler one is preferred)
  • Theories are not necessarily true (can contradict each other, only true to the extent that they are supported by research findings)
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9
Q

Cyclic Process

A

Formulate theory → derive predictions → test predictions (support or reformulate theory)

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10
Q

Population (in regards to studies)

A

Entire group of study

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11
Q

Samples (in regards to studies)

A

a part of a population or group that a researcher wants to study and male inferences about (subset drawn from population)

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12
Q

Good Samples:

A
  • Random: each person in the population has equal chances of being in the sample
  • assuming there are all kinds of differences between individuals in the group, but will average out if random selected
  • Representative: same characteristics as the population
  • i.e. age, gender, education, ethnicity
  • (Important for drawing conclusions; to the degree to which the sample is like the population)
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13
Q

Descriptive design

A
  • surveys (interviews and questionnaires)
  • Telephone surveys (pros: fast and efficient as some people don’t want to be part of the research; cons: interviewer bias as lead questions to get the responses interviewer is looking for)
  • Mail surveys (pros: avoids interviewer bias; cons: response rate as people can ignore and not return surveys)
  • Personal interview (pros: flexible; cons: costly (need proper training) and interviewer bias)
  • all descriptive designs have a potential participant response bias (not answering honestly or accurately)
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14
Q

Ways to ask questions

A
  • Likert Scale
  • range of choices on a continuum
  • usually 7 choices
  • Forced choice of 1 of 2 options
  • i.e. true or false
  • people don’t like this type because it can depend on situation
    People tend to like Likert Scale as they have more options to choose from
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15
Q

Naturalistic Observation

A
  • Careful observation and recording of behaviour in real-life settings (i.e. watching children in daycare)
  • Advantages: behaviour is observed where it typically occurs
  • Disadvantages: can’t establish cause and effect (not manipulating anything, so can’t control any variables), costly to run and observer interference (i.e. behaviour with adult present vs absent will be different).
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16
Q

Case study

A
  • in depth examination of one person, group, or event (i.e. study the deficits or changes that occur to a person who suffers brain damage.
  • Advantages: enables intensive study of rare phenomena
  • Disadvantages: generalizability of the findings is questionable (only a sample size of one; not representative), potential researcher bias, some research can’t be repeated (i.e. iron rod through phones Gage skull effect on personality)
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17
Q

Correlation

A
  • assess relationships between naturally occurring variables
  • you can measure two variables and then compute a correlation to see if there is a meaningful relationship
  • addresses questions such as:
  • how does one behaviour relate to the occurrence of another behaviour?
  • Know now behaviour, predict the other
  • Advantages: allow study of relationships that cannot be manipulated or controlled (i.e. birth order, age, etc)
  • Disadvantages: cannot assess cause and effect relationships (can only establish cause and effect when you are controlling the variables), third variable causing the relationship
    EX; as alcohol consumption increases, hand-eye coordination decreases
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18
Q

Correlation Coefficients

A
  • a range from -1 to +1
  • the further away the number is from 0, the stronger the correlation
  • i.e. -0.8 correlation is a stronger correlation than +0.2 (- and + only tells you the direction)
  • a correlation of 0 means no correlation between the two variables
  • correlation is not causation (cause and effect relationship)
  • i.e. does weekly number of drownings in Canada cause weekly ice cream consumptions to increase? or weekly drownings causing ice cream consumptions to increase?
  • a third factor/variable causing the relationship (i.e. summer, hot temperature)
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19
Q

Positive Correlation

A
  • one variable increases, the other increases

i. e. cancer rate increases as the number of cigarettes smoked a day increases (does not imply cigarettes causes cancer

20
Q

Negative Correlation

A
  • one variable increases, the other decreases

i. e. as self-esteem increases, suicide rate decreases (does not imply low self-esteem causes suicide)

21
Q

Research Design: the experiment

A

Assess cause-effect relationships between 2 or more variables

  • researcher manipulates one variable
  • i.e. amount of alcohol consumption
  • researcher then measures whether this variable produces changes in another variable
  • i.e. hand-eye coordination
  • researcher attempts to control for other factors that might influence the result
  • i.e. BMI, food consumption, natural alcohol tolerance, etc
22
Q

Why Do We Care About Cause and Effect?

A
  • Do treatments really work?
  • Compare experimental group to control group
  • i.e. when studying the effectiveness of medication; compare groups with no medication vs. medication group (verify if chances for symptoms to occur randomly)
23
Q

Independant Variable (IV)

A

The variable manipulated by the experimenter

  • possible to have more than one independent variable
  • i.e. alcohol consumption
24
Q

Dependant Variable (DV)

A

Variable affected by the independent variable

- i.e. hand-eye coordination

25
Q

Good Experiments Have High…

A
  • reliability
  • internal validity
  • external validity
  • construct validity
26
Q

Reliability

A
  • stability and consistency over time

* if you redo the experiment, you will have the same results

27
Q

Internal Validity

A
  • degree to which the experiment supports causal conclusions
  • the IV truly causes the changes in the DV
  • confidence in research findings (experiment designed and conducted well)
28
Q

External Validity

A
  • you can generalize your results to other populations, settings and conditions
  • representative sample
29
Q

Construct Validity

A
  • your measure is truly the variable you want to assess

* test must relate to what you want to measure

30
Q

Ways to do Research: setting, data, design

A 
Setting:
 - field study
 - lab
Data:
 - self-report (surveys and interviews)
 - observation
Design: 
 - case study
 - correlation
 - experimental
31
Q

Ways to do Research Example #1:
Subjects are randomly assigned to watch either a violent or a non violent video and then are watched for aggression while playing with large Bobo dolls in the lab

A

Setting: lab
Data: observation (looking at how aggressive the children are to the object)
Design: experimental (watching violent or nonviolent videos = manipulation of variables)

32
Q

Ways to do Research Example #2:

The relation between birth order and the amount of aggression on the school playground is assessed during recess

A

Setting: field study
Data: observation (amount of aggression) and self-report (birth order)
Design: correlational (no manipulation; can’t conclude that birth order affects aggression)

33
Q

Descriptive Statistics

A

describes the data set

  1. measures of central tendency (mean, mode, median)
  2. measures of variability (range, variances, standard deviation)
34
Q

Inferential Statistics

A

tests the hypotheses to make conclusions

35
Q

Null Hypothesis Testing

A
  • assume there are no differences between groups
  • all conditions are the same
  • the groups won’t all have the exact same numbers
  • if there are no real differences, how much would they differ just by chance?
  • we use statistics to determine what size of a difference is likely by chance
  • if the differences between our groups is larger than what we had expected by chance, we reject the idea that our conditions are all the same (i.e. reject null hypothesis)
  • conclude we have real group difference (i.e. suppler the alternative hypothesis meaning there is a difference between the groups)
36
Q

Mode

A

Most frequently occurring response (possible to have more than two modes = bimodal)
- i.e. (5,5,6,7,8,9,10) = 5

37
Q

Median

A

The middle response after arranging from lowest to highest

- i.e. (5,5,6,7,8,9,10) median = 7

38
Q

Mean

A

the (mathematical) average of responses
= (sum of all scores) / (number of responses)
- i.e. (5+5+6+7+8+9+10)/7 = 7.14

39
Q

Variability in Data

A

measures of variability provide information about the spread of scores

40
Q

Range

A

highest score - lowest score

* looking at our previous example, highest score is 10 and lowest score is 5, so the range is 10 - 5 = 5

41
Q

Variance

A

how much on average each score varies from the mean

= sum of [(each score -mean)squared] / number of responses

42
Q

Standard Deviation

A

S.D. = square root of the variance

43
Q

The Normal Curve

A

symmetrical about the mean (produces “bell shape”)

  • occurs when mean = median = mode for a data set
  • can determine the percentile that falls between certain standard deviation
  • mean is the midpoint where the curve is symmetrical (50% above and below mean)
44
Q

Standard Score

A

Z = (score - mean) / standard deviation

  • allows one to compare different distribution (measure how many standard deviations
  • the Z score equals the standard deviation on a normal curve
45
Q

Ethics: research with humans

A
  • informed consent
  • process (explain what participants will go through)
  • potential risks (explain the risks in the study)
  • freedom to withdraw from study without penalty
  • freedom from coercion (must not be forced)
  • guarantee confidentiality and anonymity
  • i.e. publish research with mentioning any participants’ names
  • ethical issues:
  • when should deception be used? (some participants may be angered by this)
  • when should “risky” studies be done? (if potential benefits outweigh risks = allowed)
46
Q

Ethics: research with animals

A
  • only when necessary
  • only when data critical to helping humans
  • i.e. increase human longevity
  • maintain health of the animals in experiments and animal housing
  • humane treatment is essential
  • animals are put down after the research
  • think its the humane way to do (end any animal suffering caused by the research; i.e. blindness, illness)

PSYCHOL 1000 (3 decks)

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