![]() As the contexts change, theyĪre asked to pay attention to the units for each. In this lesson, students are engaged in making sense of problems and solving them. Reference to the context in which the data were gathered. (interquartile range), as well as describing any overall pattern and any striking deviations from the overall pattern with They provide a quantitative measure of center (median) and of variability Number of observations and describing the nature of the attribute under investigation. Students summarise numerical data sets in relation to their context. Numerical data set summarises all of its values with a single number, while a measure of variation describes how the In this lesson, students develop an understanding of statistical variability, in particular, recognising that a measure of center for a While these are aligned to the NY Common Core Learning Standards, the activities align to the Victorian Curriculum content descriptions. This lesson, Describing Variability using the IQR is from the Engage NY resource which is part of the New York State Education Department website. Ask students to report their findings to the class and discuss. Outlier), commenting on any similarities and differences. Compare the two five-number summaries (including/excluding the.Calculate the five-number summary including the outlier.Represents, they can use a value for the outlier so that it is Add an outlier to the data set and show reasoning about why theĭata is classified as an outlier.Produces the box-plots the students were originally given. ![]() Calculate the five-number summary to check that the data set.Create a data set with an even/odd number of scores or create Challenge students byĪsking them to create a data set with a specific number of scores. Mean in relation to a potential data set. Summary and encourage them to consider what these numbers Support students by prompting them to first state the five-number Create a data set that would result in each of the box-plots given.To discuss what the box-plots could represent, before revealing the Provide students with a variety of box-plots from real-life scenarios.Īsk students to identify what the data could represent and the The next stage in this progression is to construct and interpret box-plots and use them to compare data sets. Upper fence outlier value = Q 3 + 1.5 × IQR (any value equal to or greater than this is an outlier) Lower fence outlier value = Q 1 – 1.5 × IQR (any value equal to or less than this is an outlier) An outlier is defined as a value that is at least 1.5 × IQR above or below the upper and lower quartiles respectively (☑.5 × IQR is used as the conventional value). It is not sufficient to deduce that a value is an outlier because it seemingly doesn’t appear to fit in with the rest of the data. To determine if a data value is an outlier, students must understand how to identify them. The following lesson, Beware of Outliers, could be used to investigate the effect of outliers on both the mean and the median. ![]() The median is used in box plots as the measure of centre, as opposed to the mean, as it is a more meaningful measure when outliers are present. The IQR is an important measure of spread as it uses only the middle 50% of the data values so that any outliers will not impact the spread of the data. a quarter of the data lie above this value or three quarters of the data lie below this value. The upper quartile ( Q U or Q 3) is the 75% mark of the data set, i.e. a quarter (25%) of the data lie below this value). ![]() The lower quartile ( Q L or Q 1) is the 25% mark of the data set, i.e. To determine the IQR, students must first determine the upper and lower quartiles. These are specifically selected to enable us to determine the centre of the data (median) as well as the spread of the data (range and IQR) by minimising the effect of outliers. The five-number summary is a collection of descriptive statistics that are used to give us a more complete analysis of data. An outlier is a data value that is significantly different from the other data values within a set. Students will also investigate the effect of outliers. They will use the five-number summary statistics (minimum, lower quartile, median, upper quartile and maximum) and associated box plot to analyse the centre and spread of data. At this level, students will determine quartiles and calculate the Interquartile range (IQR) of a data set.
0 Comments
Leave a Reply. |
Details
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |