Download Moving from broad research

Descriptive
Statistics
Printing information at:
www.msu.edu/service/mlab.web
Class website:
www.msu.edu/course/psy/475/
Moving from broad research


Begin with broad question
Generate specific hypothesis
 Narrow
basic topic
 Specific prediction about relationship

Operationalize hypothesis
 How

will we measure the constructs in our hypothesis
How you operationalize hypothesis may lead to different
results
Types of variables

Categorical variables (also called nominal)
 Has
discrete categories
 Ex: variable = sex (1=female, 2=male)


Values assigned to categories are meaningless
Continuous variables
 Many
levels or values that have meaning
Three types of continuous variables

Ordinal
 Numbers
indicate order but distance between
numbers not equal
 Ex: race winners; birth order

Interval
 Distance
between numbers equally spaced
 Ex: temperature; extraversion

Ratio
 Includes
a value of zero which indicates the absence
of a quality
 Ex: income
Continuous or Categorical

Many psychological variables are rating
scales
 Ex:
1=not at all, 2=somewhat, 3=moderately,
4=very much, 5=extremely
 Each case falls into one of these categories
 But we assume that the distance between 1 &
2 is equal to the distance between 4 & 5
 So treat this as a continuous variable
Continuous or Categorical

Rule of thumb with rating scales
2
categories: categorical
 3 categories: either depending on number of cases in
each category


If number of cases in each category fairly equal, ok to
treat as categorical
If number of cases in each category unequal, treat as
continuous
 4+
categories: continuous (approximates a
continuum)

Exception: if variable with 4 categories is truly
categorical (e.g., marital status, state live in)
Statistics Terms

Population
 Every
member in a group that you want to
study

Sample
 Representative
subset of the whole
population

Case
 Single
item or individual in your sample
Descriptive Statistics: Frequency
Distribution

Choose handful blocks:
 10”
 8”
 8”
 10”
 6”
 4”
 10”
Frequency Distribution: Summarize
Data

Length
10”
8”
6”
4”
# Blocks
3
2
1
1
Descriptive Statistics: Central
Tendency

Mean
 Arithmetic

Mode
 Most

average
frequently occurring value
Median
 Value
of the middle case in the sample if
cases arranged in order from smallest to
largest
Uses for Measure of Central Tendency

Usually the mean is the best measure

•
It takes into account the values of all the cases in
the sample, unlike the mode and median
When the mean is not the best measure of
central tendency
When there are outliers (extreme values)
1.
•
•
Will skew the mean towards the outlier
So use median instead; not influenced by outliers
When your data are categorical
2.
•
•
Then the mean is not meaningful
Use the mode instead
Measures of variance
Tells you how much the values of your
variable are spread out (vary)
 The average deviation from the mean
 Standard deviation & variance

Variance & Standard Deviation

Calculate by:
 Getting
sample mean
 Subtract each value from the mean to get deviation
 Square deviation so all signs positive
 Take the average of squared deviations
 Variance
is not in original units (is inches squared)
 Can take the square root of the variance to get the
standard deviation, which is in our original units
(inches)