Wk 6 Part 2: Data Visualisation Flashcards
What is data visualisation?
To understanding quantitative data, first to visualise the distributions of the variables and relationships between them.
- Use SPSS
What are 2 cautions with data visualisation?
- If we look long and hard enough, then we will find a relationship that is “significant” by chance even if there are actually no relationships.
- Don’t just look for any pattern - make it relevant to your research question
When exploring the distribution of a single numeric variable (numeric variables), what are 4 features that we want to describe?
- Location
- Spread
- Shape
- Deviations from the overall pattern.
What is the data visualisation for nominal variable?
Nominal variable –> Bar chart
What is the data visualisation for scale variable?
- Box plot
- Histogram
What are 5 features of histogram?
- Histograms show the estimated density of the distribution for each bin of values.
- A bin is a bar in a histogram
- Good picture of location, spread and shape of a distribution
- The direction of skewing is the tail
- Useful for visualising large numbers of observations
- Somewhat subjective (based on number of bins)
- Difficult to compare >2 groups
What are density plots?
Density plots show a line for the estimated density of the distribution at each value.
What are 7 features of quartiles and percentiles?
- 0.25 quantile = first quartile
- 0.75 quantile = third quartile
- Interquartile range = between first & third quartile
- 0.50 quantile (or 50th percentile) = median
- 0.00 quantile = minimum
- 1.00 quantile = maximum
- We can calculate other quantiles or percentiles from data too.
What is the first quartile?
0.25 quantile
What is the third quartile?
0.75 quantile
What is the interquartile range?
between first & third quartile
What is the median?
0.50 quantile (or 50th percentile)
What is the minimum?
0.00 quantile
What is the maximum?
1.00 quantile
Boxplot shows the _____ quartiles
five