Statistics level 1
We will be finishing Bivariate Data and then hopefully moving on to Multivariate Data.
Both of these standards count towards level 1 LITERACY
In statistics, bivariate data is data that has two variables. The quantities from these two variables are often represented using a scatter plot. This is done so that the relationship (if any) between the variables is easily seen. For example, bivariate data on a scatter plot could be used to study the relationship between stride length and length of legs.
Students need to be familiar with the statistical enquiry cycle to investigate a given multivariate data set, which involves:
- investigating data that has been collected from a survey situation
- posing an appropriate comparison question using a given multivariate data set
- selecting and using appropriate display(s)
- giving summary statistics such as the five summary values (minimum, maximum, median, quartiles)
- discussing features of distributions comparatively, such as shape, middle 50%,shift, overlap, spread, unusual or interesting features
- communicating findings, such as informal inference and supporting evidence, in a conclusion.
- Positive relationship: A positive gradient, if one value goes up so does the other.
- Negative relationship:A negative gradient, if one value goes up the other goes down.
- No relationship: data looks random or can't decide between negative or positive trend line.
- Manage sources of variation: steps to make measuring/collecting the data as accurate as possible.
- Non-linear relationship: a relationship that is not linear (a line), so a curve of some sort.
- Cleaning data: the process of detecting and correcting (or removing) corrupt or inaccurate records from a data set.
Achievement: Investigate a given multivariate data set using the statistical enquiry cycle.
Achievement with Merit: Investigate a given multivariate data set using the statistical enquiry cycle, with justification.
Achievement with Excellence: Investigate a given multivariate data set using the statistical enquiry cycle, with statistical insight.