PSY 241 Study Guide - Final Guide: Statistic, Statistical Inference, Statistical Parameter
5 May 2018
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Chapter 1
Definitions:
★ Statistics: a set of mathematical procedures for organizing, summarizing and interpreting
information
★ Population: entire set of the individuals of interest for a particular research question
★ Sample: set of individuals selected from a population, usually intended to represent the
population in a research study
★ Variable: characteristic or condition that changes or has different values for different
individuals
★ Data: measurements or observations
★ Data set: collection of measurements or observations
★ Datum: single measurement or observation and is commonly called a score or raw score
★ Parameter: a value, usually a numeric value, that describes a population. A parameter is
usually derived from measurements of the individuals in the population
★ Statistic: a value, usually a numerical value, that describes a sample. A statistic is
usually derived from measurements of the individuals in the sample
★ Descriptive statistics: statistical procedures used to summarize, organize and simplify
data
★ Inferential statistics: consists of techniques that allow us to study samples and then
make generalizations about the populations from which they were selected
★ Sampling error: naturally occurring discrepancy, or error, that exists between a sample
statistic and the corresponding population parameter
★ Correlation method: two different variables are observed to determine whether there is a
relationship between them
★ Experimental method: one variable is manipulated while another variable is observed
and measured. To establish a cause-and-effect relationship between the two variables,
an experiment attempts to control all other variables to prevent them from influencing the
results
★ Independent variable: the variable that is manipulated by the researcher. In behavioural
research, the independent variable usually consists of the two (or more) treatment
conditions to which subjects are exposed. The independent variable consists of the
antecedent conditions that are manipulated prior to observing the dependent variable
★ Dependent variable: the variable that is observed to assess the effect of the treatment
★ Control condition: doesn’t receive the experimental treatment. Instead, they either
receive no treatment or they receive a neutral, placebo treatment. The purpose of a
control condition is to provide a baseline for comparison with the experimental condition.
The individuals in the control condition are often called the control group
★ Experimental condition: do receive the experimental treatment and are often called the
experimental group
★ Quasi-independent variable: in a non-experimental study, the “independent” variable that
is used to create the different groups of scores
★ Construct (hypothetical constructs): internal attributes or characteristics that cannot be
directly observed but are useful for describing and explaining behaviour
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★ Operational definition: identifies a measurement procedure (a set of operations) for
measuring an external behaviour and uses the resulting measurements as a definition
and a measurement of an internal construct. Note that an operational definition has two
components:
○ It describes a set of operations for measuring a construct
○ It defines the construct in terms of the resulting measurements
★ Discrete variable: consists of separate, indivisible categories. No values can exist
between two neighbouring categories
★ Continuous variable: there are an infinite number of possible values that fall between
any two observed values. A continuous variable is divisible into an infinite number of
fractional parts
★ Real limits: boundaries of intervals for scores that are represented on a continuous
number line. The real limit separating two adjacent scores is located exactly halfway
between the scores. Each score has two real limits.
○ Upper real limit: at the top of the interval
○ Lower real limit: at the bottom of the interval
★ Nominal scale: consists of a set of categories that have different names. Measurements
on a nominal scale label and categorize observations, but do not make any quantitative
distinctions between observations
★ Ordinal scale: consists of a set of categories that are organized in an ordered sequence.
Measurements on an ordinal scale rank observations in terms of size or magnitude
★ Interval scale: consists of ordered categories that are all intervals of exactly the same
size. Equal differences between numbers on the scale reflect equal differences in
magnitude. However, the zero point on an interval scale is arbitrary and does not
indicate a zero amount of the variable being measured
★ Ratio scale: an interval scale with the additional feature of an absolute zero point. With a
ratio scale, ratios of numbers do reflect ratios of magnitude
★ Confounded: variable that varies systematically along with IV that can influence the
results
★ Random assignment: each participant has an equal chance of being assigned to each of
the treatment conditions
★ Matching: ensure equivalent groups eg. researcher makes sure each group is 60%
female and 40%
★ Nonequivalent groups study: researcher cannot use random sampling
★ Pre-post study: measuring before and after IV is manipulated
★ Sigma: summation (sum of)
★ Order of operations: PEMDAS
○ 1. Parentheses
○ 2. Exponents (squaring)
○ 3. Multiplication
○ 4. Division
○ 5. Addition
○ 6. Subtraction
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Chapter 2
Definitions:
★ Frequency distribution: an organized tabulation of the number of individuals located in
each category on the scale of measurement
★ Range: difference between highest and lowest scores
★ Grouped frequency distribution: table of results
★ Class interval: groups/intervals
★ Apparent limits: eg. for a class interval of 40-49, X=40 and X=49 are apparent limits of
the interval because they form the upper and lower boundaries for the class interval
★ Axes: fixed reference line for the measurement of coordinates
★ Histogram: used when the data consists of scores that has been measured on an
interval scale, bars DO touch
★ Bar graph: used when the scores are measured on a nominal or ordinal scale (usually
non-
numerical values), bars DON’T touch
★ Polygon: used when the data consists of scores that has been measured on an interval
scale
★ Relative frequency: proportions describe the frequency (f) in relation to the total number
(N)
★ Distribution of scores:
★ Symmetrical distribution: it is possible to draw a vertical line through the middle so that
one side of the distribution is a mirror image of the other
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Document Summary
Definitions: individuals information population in a research study. Statistics: a set of mathematical procedures for organizing, summarizing and interpreting. Population: entire set of the individuals of interest for a particular research question. Sample: set of individuals selected from a population, usually intended to represent the. Variable: characteristic or condition that changes or has different values for different. Data set: collection of measurements or observations. Datum: single measurement or observation and is commonly called a score or raw score. Parameter: a value, usually a numeric value, that describes a population. Statistic: a value, usually a numerical value, that describes a sample. Descriptive statistics: statistical procedures used to summarize, organize and simplify. Sampling error: naturally occurring discrepancy, or error, that exists between a sample. Correlation method: two different variables are observed to determine whether there is a. Experimental method: one variable is manipulated while another variable is observed data.
