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Lecture 1

PSYC 1010 Lecture Notes - Lecture 1: Statistical Inference, Statistic, Descriptive Statistics

Course Code
PSYC 1010
David Stanley

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The practice of collecting, analyzing, interpreting, and reporting
numerical data
Two Branches of Statistics
Descriptive statistics
o Organizes, summarizes, and communicates a group of
numerical information
Inferential statistics
o Using data collected from a representative group to draw
conclusions about a population
Descriptive Statistics
Tend to take the form of tables, graphs, or single numbers that
consolidate a large amount of information
Inferential Statistics
Techniques that use sample data to draw general conclusions about
the larger population
o Measuring everyone in the population is usually impossible
o Use sample statistics to infer what the population parameter
is likely to be
Populations and Samples
Population: the set of observation of interest in a particular study
Sample: A set of observations drawn from a population of interest
for inclusion in a study
Parameter: A (usually numerical) value that describes a whole
Statistic: A (usually numerical) value that describes a sample of the
Sampling Error
Sampling error is the _____ between a sample statistic and a
population parameter

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Basic Research Design
Pick a population of interest (e.g., students)
o Decide how you will recruit a sample (who, how many, etc…)
Pick a variable of interest (e.g., study habits)
o Decide how you will measure the variable
Turning Observations into Variables
o Observing people’s physical environment, attitudes, and
behaviour leads to variables – data that can take on different
values (vary)
Step 1: Define population and variables of interest

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Step 2: Descriptive Statistics
Sample A: Average study time =
Sample B: Average study time =
Step 3: Inferential Statistics
Sample data show
Two possibilities
There is no real difference between the groups and sample
difference due to ________
There is a difference between the groups and the sample data
reflects this
Use _______ to decide between the two alternatives
Turning observations into Variables
Discrete variables
oVariables that can only take on only specific values (e.g.,
whole numbers)
oMeasures “how many”?
how many letters are in your name?”
Continuous variables
o Can take on a full range of values
o Measures “how much”?
“how tall are you?”
Always Discrete
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