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It's All About Variables! 2
Table of Contents
Population versus Sample...................................................................................................................................3
Selecting Samples...............................................................................................................................................3
Simple Random Sample (SRS)......................................................................................................................3
Stratified Random Sampling..........................................................................................................................3
Cluster Sampling............................................................................................................................................3
Systematic Sampling......................................................................................................................................3
Convenience Sampling..................................................................................................................................3
Self-Selected Samples....................................................................................................................................3
Bias..........................................................................................................................................................................4
VARIABLES ­ Things that vary.............................................................................................................................5
Experiment Design ­ Observational or Experimental........................................................................................5
NUISANCE VARIABLES.................................................................................................................................5
CONTROLLING SUBJECT NUISANCE VARIABLES.............................................................................5
CONTROLLING SITUATION NUISANCE VARIABLES.........................................................................6
CONFOUNDING FACTORS........................................................................................................................6
FAULTS.........................................................................................................................................................6
What's Normal?.......................................................................................................................................................7
Standardised Values (z-scores)...........................................................................................................................7
Significance Theory............................................................................................................................................8
P value - Significance ....................................................................................................................................8
From Population to Samples ­ The Proportion..............................................................................................8
Tests for Categorical Variables..............................................................................................................................10
REPORT...........................................................................................................................................................…read more

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It's All About Variables! 3
Population versus Sample
Populations are all the things we are interested in; they can be all people, cars, cats or toothpicks. We can be
interested in more than one population at the same time.
Samples are a random selection of a proportion of the population used to test the hypothesis or research
question against.…read more

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It's All About Variables! 4
Bias
Who organised the study?
· Was the study is organised by a company or people with a vested interest in getting a certain result.
e.g. CSR organising a study on whether too much sugar is bad for your health.
Who conducted the study?
· Was the study conducted by a company or people who have a vested interest in getting a certain
result. e.g. Out of work sugar producers trying to get a factory re-opened conduct the study.…read more

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It's All About Variables! 5
VARIABLES ­ Things that vary.
Categorical ­ can contain any value from a range of values. e.g. Sex = F, M (or 0 for F and 1 for M), range of
10,20,30,40 = each time it can contain any one of these numbers.
Metric ­ can contain only one numeric value only e.g. Score = 35.6, How much do you weigh in Kg's = 84.
Variables can be either Independent (IV) or Dependent (DV).
CHANGE EFFECT
relationship
IV DV
e.g.…read more

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It's All About Variables! 6
Matched Pairs Design
use pairs of participants carefully matched on all major subject nuisance variables
for each pair, one is randomly assigned to each of the treatment conditions
use this avoids practice effects, but
you need to identify all major nuisance variables and find several carefully matched pairs, e.g.…read more

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It's All About Variables! 7
What's Normal?
Example: 70 out of 1000 said yes.
Proportion = Frequency/ Total Number
70 / 1000 = 0.07
Percentage = proportion x 100
0.07 x 100 = 7%
The normal distribution is described as a "symmetric, bell shaped curve". For any given mean and standard
deviation you can draw a normal curve, and regardless of what the mean and standard deviation happen to
be, 95% of values fall within two standard deviations of the mean.…read more

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It's All About Variables! 8
Significance Theory
P value - Significance
Tells us what the chance is of getting a proportion as high/low in the sample if the proportion was still the
known proportion.
0.1 = 1 chance in 10, 0.01 = 1 chance in 100, 0.001 = 1 chance in 1000
From Population to Samples ­ The Proportion.
In the above histogram and percentiles chart the sample proportions
cluster around .30 and 50% of sample proportions fall between .25
and .33.…read more

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It's All About Variables! 9
EXERCISE 3.2 from Foundations of Statistics, 2nd Edition
In 2006, 62% of all AFL players lived in Victoria. Suppose we took a random sample of 25 AFL players from this
population.
We would expect the sample
proportion of AFL players who
lived in Victoria to be somewhere
around 0.62, but not necessarily
exactly equal to 0.62.
Each block represents the
proportion of players who live in
Victoria in one random sample of
25 AFL players.…read more

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It's All About Variables! 10
Tests for Categorical Variables
Describing the distribution of a single categorical variable.
SPSS ­ Analyze/Descriptive Statistics/Frequencies
Use Pie chart for 2 or 3 categories
Use Bar chart for 3 or more categories
What you need to know.
Total of participants in sample = 416. Always use the valid percent column for percentages.…read more

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