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Lecture

# Chapter 2

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University of Toronto Scarborough

Psychology

PSYA01H3

Steve Joordens

Fall

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CHAPTER 2: METHODS IN PSYCHOLOGY
Empiricism: How to Know Stuff
− dogmatism: the tendency for people to cling to their assumptions
− empiricism
− The belief that accurate knowledge can be acquired through observation.
The Scientific Method
− scientific method
− A set of principles about the appropriate relationship between ideas and evidence.
− theory
− A hypothetical explanation of a natural phenomenon.
− rule of parsimony: when scientists set out to develop a theory they start with the simplest one
− 14th-century logician William Ockham suggested that it makes sense to start with the simplest theory possible and then make the theory more
complicated only if we must
− hypothesis
− A falsifiable prediction made by a theory.
− even if the theory wasn't disproved by your observation there always remains some chance that it will be disproved by some other observation
− when evidence is consistent with a theory it increases our confidence in it, but it never makes us completely certain
The Art of Looking
− empirical method
− A set of rules and techniques for observation.
− method: technologies that enhance the powers of the senses
− three things make people difficult to study:
− complexity: scientists can barely begin to say how the 500 million interconnected neurons that constitute the brain give rise to the thoughts,
feelings, and actions that are psychology's concerns
− variability: no two individuals ever do, say, think, or feel exactly the same thing under exactly the same circumstances, which means that
when you've seen one, you've most definitely seen them all
− reactivity: people often think, feel, and act one way when they are being observed and a different way when they are not
− methods of observation allow psychologists to determine what people do, and methods of explanation allow them to determine why people do
it
Observation: Discovering What People Do
− to observe is to use one's senses to learn about the properties of an event or an object
Measurement
− when we want to measure, we must always do two things—define the property we wish to measure and then find a way to detect it
Defining and Detecting
− operational definition
− A description of a property in concrete, measurable terms.
− measure
− A device that can detect the condition to which an operational definitions refers.
− electromyograph (EMG)
− A device that measures muscle contractions under the surface of a person's skin.
Validity, Reliability, and Power
− good measures have three properties: validity, reliability, and power
− validity
− The extent to which a measurement and a property are conceptually related.
− reliability
− The tendency for a measure to produce the same measurement whenever it is used to measure the same thing.
− power
− The ability of a measure to detect the concrete conditions specified in the operational definition.
Demand Characteristics
− demand characteristics
− Those aspects of an observational setting that cause people to behave as they think they should.
− they are called demand characteristics because they seem to “demand” or require that people say and do things that they normally might not
− naturalistic observation
− A technique for gathering scientific information by unobtrusively observing people in their natural environments.
− naturalistic observation isn't always a viable solution to the problem of demand characteristics − first, some of the things psychologists wants to observe don't occur naturally
− second, some of the things that psychologists want to observe can only be gathered from direct interaction with a person
− people are less likely to be influenced by demand characteristics when they cannot be identified as the originators of their actions, and
psychologists often take advantage of this fact by allowing people to respond privately or anonymously
− another technique that psychologists use to avoid demand characteristics is to measure behaviors that are not susceptible to demand
− behaviors are unlikely to be influenced by demand characteristics when people don't know the demand and the behavior are related
− one of the best ways to avoid demand characteristics is to keep the people who are being observed from knowing the true purpose of the
observation
− when people are “blind to the purpose of an observation, they can't behave the way they think they should behave because they don't know
how they should behave
− psychologists sometimes use cover stories: misleading explanations that are meant to keep people from discerning the true purpose of an
observation
− the psychologist might use filler items: pointless measures that are designed to mislead you about the true purpose of the observation
Observer Bias
− expectations can influence observations
− expectations can influence reality
− double-blind
− An observation whose true purpose is hidden from both the observer and the person being observed.
Descriptions
− frequency distribution
− A graphical representations of measurements arranged by the number of times each measurement was made.
− although a frequency distribution can have any shape, a common shape is the bell curve, which is known as the Gaussian distribution or the
normal distribution
− normal distribution
− A mathematically defined frequency distribution in which most measurements are concentrated around the middle.
− the normal distribution is symmetrical, has a peak in the middle, and trails off at both ends
Descriptive Statistics
− descriptive statistics: brief summary statements that capture the essential information from a frequency distribution
− two important kinds of descriptive statistics: those that describe the central tendency of a frequency distribution and those that describe the
variability in the frequency distribution
− descriptions of central tendency are statements about the value of the measurements that tend to lie near the center or midpoint of the
frequency distribution
− the three most common descriptions of central tendency are the mode, the mean, and the median
− mode
− The value of the most frequently observed measurement.
− mean
− The average value of all the measurements.
− median
− The value that is “in the middle”--i.e. greater than or equal to half the measurements and less than or equal to half the measurements.
− in a normal distribution, the mean, median, and mode all have the same value, but when the distribution is not normal, these three descriptive
statistics can differ
− the frequency distribution of your measurements would not be normal, but positively skewed
− the mode and the median of a positively skewed distribution are much lower than the mean because the mean is more strongly influenced by
the value of a single extreme measurement
− when distributions become skewed, the mean gets dragged off toward the tail, the mode stays at home at the hump, and the median goes to
live between the two
− when distributions are skewed, a single measure of central tendency can paint a misleading picture of the measurements
− whereas description of central tendency are statements about the location of the measurements in a frequency distribution, descriptions of
variability are statements about the extent to which the measurements differ from each other
− the simplest description of a variability is the range
− range
− The value of the largest measurement in a frequency distribution minus the value of the smallest measurement.
− when the range is small, the measurements don't vary as much as when the range is large
− the range is easy to compute, but like the mean it can be dramatically affected by a single measurement
− standard deviation
− A statistic that describes the average difference between measurements in a frequency distribution and the mean of that distribution.
− two frequency distributions can have the same mean, but very different ranges and standard deviations
Explanation: Discovering Why People Do What They Do
− although scientific research always begins with the measurement of properties, its ultimate goal is the discovery of causal relationships
between properties
− measurements tell us what happened, but not why
Correlation
Patterns of Variation − first, you measured a pair of variables
> variable
A property whose value can vary across individuals or over time.
− second, you made a series of measurements rather than just one
− third, you tried to discern a pattern in your series of measurements
> pattern of variation: values that vary
> correlation
Two variables are said to “be correlated” when variations in the value of one variable are synchronized with variations in the value of the other.
− correlations not only describe the past, but also allow us to predict the future
− when two variables are correlated, knowledge of the value of one variable allows us to make predictions about the value of the other variable
− a positive correlation describes a relationship between two variables in “more-more” or “less-less” terms
− a negative correlation describes a relationship between two variables in “more-less” or “less-more” terms
Measuring Correlation
− correlation coefficient
− A measure of the direction and strength of a correlation, which is signified by the letter r.
− like most measures, the correlation coefficient has a limited range
− the value of r can range from -1 to 1, and numbers outside that range are meaningless
− what numbers inside that range mean:
− perfect positive correlation: if every time the value of one variable increases by a fixed amount the value of the second variable also increases
by a fixed amount and r = 1
− perfect negative correlation: if every time the value of one variable increases by a fixed amount the value of the second variable decreases by
a fixed amount and r = -1
− uncorrelated: if every time the value of one variable increases by a fixed amount the value of the second variable does not increase or
decrease systematically and r = 0
− perfect correlations show patterns of variations that are perfectly synchronized and without exceptions
− such correlations are extremely rare in real life
− two variables can have a perfect correlation, a strong correlation, a moderate correlation, or a weak correlation
− the correlation coefficient is a measure of both the direction and strength of the relationship between two variables
− the sign value of r (between 0 and 1) tells us about the number of exceptions and hence about how confident we can be when using
correlation to make predictions
Causation
− philosopher Immanuel Kant suggested that people come into the world with cause-detectors built into their brains
− sometimes we see causal relationships that don't actually exist
− just as we see causal relationships that don't exist, we sometimes fail to see causal relationships that do exist
The Third-Variable Problem
− natural correlation
− A correlation observed in the world around us.
− although such observations can tell us whether two variables have a relationship, they cannot tell us what kind of relationship these variables
have
− third-variable correlation
− The fact that two variables are correlated only because each is causally related to a third variable.
− when we observe a natural correlation, the possibility of the third-variable correlation can never be dismissed
− matched samples
− A technique whereby the participants in two groups are identical in terms of a third variable.
− matched pairs

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