SPPS TEST THINGS TO KNOW:
Units of analysis – the what or who that is being studied (one thing)
rows
Variable – a measured property of each of the units of analysis
coloms
Nominal level of measurement:
- group classifications
- no meaningful ranking possible (i.e. 3 is not ‘more’ than 2)
- Numerical coding arbitrary (but necessary in SPSS
Ordinal level of measurement (order)
- Meaningful ranking/ordering (3 is ‘more’ than 2)
- BUT: distance between categories unknown/not equal (e.g. difference between 1 and
2 not equal to difference between 2 and 3)
“a horserace without a stopwatch” you know the winner, but don’t know the
exact time difference
Interval level of measurement
- meaningful ranking (17 is more than 16)
- Distances are equal (e.g. difference between 15 and 17 is equal to difference
between 20 and 22)
Ratio level of measurement
- All properties of interval (ranking & equal distances)
- Absolute & meaningful zero point
Outlier – value that is far away from the rest of our distribution, a lot higher or lower it
sticks out
- Can ruin the interpretate value of the mean
- Use median the median seems more useful here (not sensitive to outlier)
Skewed distribution
- Left: the mean is shifted to the left in a negatively skewed distribution
- Right: the mean is shifted to the right in a positively skewed distribution
look at the way it stretches out (left/right)
, The mean
- Can only be used for interval/ratio variables
- Most useful for describing (more or less) normally distributed variables
The median
- Can be used for ordinal or interval/ratio variables
- Often used for interval/ratio variables that have skewed distributions
The mode
- Can be used for nominal, ordinal or interval/ratio variables
Independent variable – column (top of the table)
When calculating percentages, we always calculate column percentages the categories of
the independent variable sum up to 100%
SPSS OVERVIEW:
TO DETERMINE THE RELATIONSHIP IN A CROSSTAB:
1. Put the independent variable in the columns (i.e. its categories make up the
columns) and the dependent variable in the rows
2. Calculate percentages of columns
3. Compare percentages horizontally within the categories of the dependent variable
Altering the dataset:
- Select cases (data - select cases – if satisfied – variable = x)
- Recode into different variable (transform – recode into different variables – add
name – old and new values – variable view – add labels)
Units of analysis – the what or who that is being studied (one thing)
rows
Variable – a measured property of each of the units of analysis
coloms
Nominal level of measurement:
- group classifications
- no meaningful ranking possible (i.e. 3 is not ‘more’ than 2)
- Numerical coding arbitrary (but necessary in SPSS
Ordinal level of measurement (order)
- Meaningful ranking/ordering (3 is ‘more’ than 2)
- BUT: distance between categories unknown/not equal (e.g. difference between 1 and
2 not equal to difference between 2 and 3)
“a horserace without a stopwatch” you know the winner, but don’t know the
exact time difference
Interval level of measurement
- meaningful ranking (17 is more than 16)
- Distances are equal (e.g. difference between 15 and 17 is equal to difference
between 20 and 22)
Ratio level of measurement
- All properties of interval (ranking & equal distances)
- Absolute & meaningful zero point
Outlier – value that is far away from the rest of our distribution, a lot higher or lower it
sticks out
- Can ruin the interpretate value of the mean
- Use median the median seems more useful here (not sensitive to outlier)
Skewed distribution
- Left: the mean is shifted to the left in a negatively skewed distribution
- Right: the mean is shifted to the right in a positively skewed distribution
look at the way it stretches out (left/right)
, The mean
- Can only be used for interval/ratio variables
- Most useful for describing (more or less) normally distributed variables
The median
- Can be used for ordinal or interval/ratio variables
- Often used for interval/ratio variables that have skewed distributions
The mode
- Can be used for nominal, ordinal or interval/ratio variables
Independent variable – column (top of the table)
When calculating percentages, we always calculate column percentages the categories of
the independent variable sum up to 100%
SPSS OVERVIEW:
TO DETERMINE THE RELATIONSHIP IN A CROSSTAB:
1. Put the independent variable in the columns (i.e. its categories make up the
columns) and the dependent variable in the rows
2. Calculate percentages of columns
3. Compare percentages horizontally within the categories of the dependent variable
Altering the dataset:
- Select cases (data - select cases – if satisfied – variable = x)
- Recode into different variable (transform – recode into different variables – add
name – old and new values – variable view – add labels)
