Presentation of quantitative data
Cards (8)
- Bar chartsThe frequency of each variable is represented by the height of bars.
- Used when data is divided into categories.
- Bars are separated to denote that they are dealing with separate conditions.
- Histogram
- A type of graph which shows the frequency but unlike a bar chart, the areas of the bars (not just height) represents frequency.
- X-axis must start at a true zero and scale is continuous.
- Bars touch each other, showing X-axis is continuous.
- Scattergram
- Type of graph that represents the strength and direction of the relationship between co-variable in a correlational analysis.
- Either co-variable occupies x-axis and other y-axis.
- Normal distribution
- A symmetrical spread of frequency data, that forms a bell shaped pattern.
- The mean, median and mode are all located at the highest peak.
- Most people are located in the middle area of the curve with very few people at extreme ends.
- Skewed distributionsA spread of frequency data that is not symmetrical, where data clusters to one end.
- Positive skew
- A type of frequency distribution in which the long tail is on the positive (right) side of the peak and most of the distribution is concentrated on the left.
- E.g a difficult test in which most people got low parks with only a handful of students at higher end.
- Mode remains at the peak, median is next but mean is dragged across tail (right side).
- During a positive skew why does the mean lie further down the tail (right side)?High scoring students have the effect of pulling mean to right, but median are mode are not affected by this.
- Negative skew
- A type of frequency distribution in which long tail is on the negative (left) side of peak, and most of distribution is concentrated on the right side.
- E.g A very easy test would produce a distribution where the bulk of scores are concentrated on the right, resulting in a long tail of anomalous results on the left.
- Mean is pulled to left, median in the middle and mode at the highest peak.