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CHAPTER 6
Psychological Research and Statistics
Objectives
Describe the process of psychological research
Name the different types of psychological research and some of the methodological hazards of doing research
Describe descriptive and inferential statistics
Name specific research methods used to organize data
Gathering Data
How do psychologists collect information about the topic they’ve chosen to study?
Gathering Data
Validity – extent to which an instrument measures or predicts what it is supposed to
Algebra questions would not be a valid measure of what you learned in Psych class
Gathering Data
Sample – relatively small group out of the total population
Population – an entire group as a whole Sample must be representative of the
population If a sample is not representative, then it
is biasedHow can researchers avoid bias?
Gathering Data
What does correlation mean? The degree of relatedness between
two sets of data
Two types - positive correlation & negative correlation
Gathering Data
IQ scores and academic success – positive correlation (direct relationship) The higher your IQ, the higher your
grades
Car speed and time it takes to travel somewhere – negative correlation (inverse relationship)
- as car speed increases, time it takes to reach your destination decreases
Correlations
Your turn!
Hours in the sun and chance of sunburn Positive correlation
Amount of exercise and % body fatNegative correlation
Mrs. Bird’s high school GPA and your high school GPAno correlation
Correlations
A researcher uses statistics to compute their research findings Statistics = field of mathematics that
involves the analysis of numerical data about representative sample of population
Correlation coefficient = needs to be near 1 (-/+), the closer results
are to -1 or +1 the better the relatability between the two variables
Experiments
Why do researchers choose experimentation over other research methods? Researchers can control the situation. Can establish cause and effect, only
research method in which you can
The goal of research is to prove or disprove a . . .Hypothesis
Experiments
Variables – conditions and behaviors that are subject to variation/change
Two types of variables – independent and dependent IV – manipulated variable in order to
view its effects DV – dependent upon the IV – affected
by it, the one the researcher measures
Experiments
Experimental group – consists of subjects who undergo the experimental treatment – variables are applied to this group
Control group – consists of subjects who do not receive experimental treatment Why is this group necessary?
Experiments in Psych
Avoid Researcher Bias: researcher’s desire to prove hypothesis affects results
Avoid Self-fulfilling prophecy: researcher’s desire to prove hypothesis affects results
Could be very subtle or unconscious, but researcher will treat one group slightly differenty (body language, tone of voice)
Avoiding Researcher Bias
Use double-blind = neither researcher nor subjects know what group they are in, helps reduce researcher influencing results
Confounding variables = factors that cause changes in the dependent variable that aren’t the independent variables
Quasi-Experiment (“sort of” experiment)
For example, imagine that we wanted to do a study to compare student performance. Imagine further that we scheduled two sections of the course, let students sign up for which one they wanted, and then taught one using cooperative learning and the other using standard lecture. Note that this study includes a manipulated independent variable, but it lacks random assignment of participants to conditions. The problem with this approach, of course, is that there might be differences between the two groups of students other than the style of teaching to which they were exposed. Perhaps the students who signed up for the earlier section are more “gung ho.” Or perhaps the students who signed up for the evening section are more likely to be working adults. Or perhaps the students in the 1:00 p.m. section tend to be drowsy after lunch. It is possible that differences in the dependent variable could have been caused by these differences rather than differences in teaching style.
So what’s the problem with quasi-experiments?
No random assignment! = a sort of experiment!
Other examples: boys vs girls, old vs. young
Naturalistic Observations
Naturalistic observation – viewing the subjects of an experiment in their natural habitat IMPORTANT: Subjects CANNOT
know they are being watched! Why is this important??
CASE STUDY
Case study – a scientific biography of a group or person, very in depth look at a phenomena Most use long-term research to gather
tons of data in order to generate new hypotheses
Utilize lots of different tests to collect data
ex) facial agnosia, split brain patients
Surveys
Surveys – an interview/questionnaire that gathers data on the attitudes, beliefs, and experiences of large numbers of people
Longitudinal Studies
Longitudinal studies – covers a long period of time, same subjects followed for long time and questioned at different intervals in time (ex. Age 20, 25, 30 35)
Psychologists study subjects over regular intervals for a period of years Allows for examination of
consistencies and inconsistencies as development occurs
Cross-sectional
Cross-sectional studies – individuals are organized/studied on the basis of age
Question different groups of people that represent different stages of development
Avoiding Errors
How can researchers avoid errors while doing research? self-fulfilling prophecy - Researchers finding
what they want to find, while overlooking contrary evidence
Example experiment – testing a new medicine Single Blind – subjects do not know if they
have a are in control group (placebo) or in the experimental group ( get real IV)
Double Blind – subjects AND experimenter have no knowledge of who in is experimental or control group = best option if possible to design
Smile Break
Statistics
A branch of mathematics that enables researchers to organize and evaluate the data they collect
Statistics
Descriptive statistics – listing and summarizing data in a practical and efficient way Examples – graphs, averages
Statistics
Frequency distribution – table that arranges data in a way that allows us to see how often a particular score occurs
Histogram – similar to bar graphs – always vertical & the bars always touch
Frequency polygon – no bars just lines to visually display data
Frequency Distribution
Histogram
Frequency Polygon
Central Tendency
Central tendency – a number that describes something about the “average” score Used to summarize information into statistics
Measures of CT: mean, median mode
Central Tendency
Mean – an “average” score Most commonly used measure of CT
To find the mean, you add all scores and divide by the number of scores
Central Tendency
Median – the middle score The midpoint of a set of scores, so it divides the frequency distribution into two halves
Mode – the most frequent score
Central Tendency
0, 3, 4, 4, 5, 5, 6, 7, 8, 8, 8, 9, 9, 10, 10
Mean – 6.4 Median – 7 Mode - 8
Measures of Variance
Distributions show us not only the “average” score, but also how “spread out” these scores are.
Variance – provides an index of how spread out the scores of a distribution are
Measures of Variance
Range – subtract the lowest score from the highest score
Standard deviation – a measure of distance, describing an “average” distance of every score to the mean The larger the standard deviation,
the more spread out the scores are
Standard Deviation
Inferential Statistics Used to determine whether or not the
data that researchers collect supports their hypotheses, or whether their results are merely due to chance outcomes, draw conclusions & interpret data probability & chance
If probability that results are due to chance is less than 5% ( .05), researchers can be confident in their findings (less than 1 in 20 chance)
Ethical Guidelines
Read page 59
Define for Homework, Chapter 6Population Placebo effectSample Demand characteristicsExperimental group CounterbalancingControl group ReliabilityBetween subject design Ex post factoWithin subject design BimodalConfounding variables MultimodalOperational definition Skewed distribution Random Assignments Meta-analysisExperimenter Bias