Data Handling With Ict For Bb

Data handling

Liars, damn liars and Liars, damn liars and statisticians!statisticians!

Objectives

review your own subject knowledge in this review your own subject knowledge in this area ensuring secure understanding, area ensuring secure understanding, identifying key facts and using vocabulary identifying key facts and using vocabulary accurately.accurately.

consider children’s learning styles, possible consider children’s learning styles, possible misconceptions, progression and research in misconceptions, progression and research in children’s learningchildren’s learning

evaluate teaching styles and strategies, evaluate teaching styles and strategies, resources and ICT resources and ICT

consider issues relating to Inclusion and consider issues relating to Inclusion and Differentiation, progression in learning from Differentiation, progression in learning from the FS to KS3, and Cross curricular linksthe FS to KS3, and Cross curricular links

NC requirements: 5 stages to data handling

Posing questions Posing questions Collecting data Collecting data Processing the data Processing the data Representing the data Representing the data Interpreting the dataInterpreting the data

NB: NB: Some activities involve some of these Some activities involve some of these

stages stages All these stages need learning about All these stages need learning about Some activities need to involve all 5 stages Some activities need to involve all 5 stages

Progression in sorting

Sorting Sorting Positive attribute labels (Sort first, label Positive attribute labels (Sort first, label

later)later) Positive attributes and then negation Positive attributes and then negation

(Label first then sort - red, not red)(Label first then sort - red, not red) Types of sets Types of sets

Unstructured sets (random eg toy cars)Unstructured sets (random eg toy cars) Structured sets (Compare bears – small, Structured sets (Compare bears – small,

medium & large bears in blue, red, medium & large bears in blue, red, yellow & green)yellow & green)

Additional techniques for sorting Venn diagramVenn diagram Carroll diagramCarroll diagram Decision tree Decision tree

Suggested progression

A suggested sequence for progressionA suggested sequence for progression 3D data (use the shoes!)3D data (use the shoes!) 3D representation (cubes illustrating 1-1 3D representation (cubes illustrating 1-1

correspondence)correspondence) Post it pictograms (moving towards the abstract)Post it pictograms (moving towards the abstract) Block graphs (Vertical axis and labels)Block graphs (Vertical axis and labels) Bar graphsBar graphs

Different to block graphDifferent to block graph Labelling issues – the line is labelled not the Labelling issues – the line is labelled not the

blockblock Pie chartsPie charts Line graphs (Is this suitable?)Line graphs (Is this suitable?)

ICT in data handling When can this be useful?When can this be useful? What have you seen?What have you seen? ICT dilemma – when exploring software such as ICT dilemma – when exploring software such as

Excel children will want to try these outExcel children will want to try these out This is not always the best type of chart to This is not always the best type of chart to

useuse Pie chartsPie charts

Prior knowledge?Prior knowledge? Some children will have seen this style of Some children will have seen this style of

representation and wish to emulate itrepresentation and wish to emulate it DifferencesDifferences

Pie charts use proportional Pie charts use proportional representation, not numerical representation, not numerical representation, therefore ..representation, therefore ..

Labelling size of data sample is importantLabelling size of data sample is important

ICT to present data

Using ICT opportunitiesUsing ICT opportunities 2Simple software: 2graph2Simple software: 2graph Handy graphHandy graph Data handlingData handling Line graphLine graph ExcelExcel

Asking questions and interpreting data Look at this temperature data Look at this temperature data Write a question to develop interpreting Write a question to develop interpreting

data skills for data skills for Simple questionsSimple questions Intermediate questionsIntermediate questions Difficult questionsDifficult questions

What sort of questions did you write?What sort of questions did you write? Compare questions with notes from Compare questions with notes from

previous lecture previous lecture

Interpretation tools

Mathematics needed to augment Mathematics needed to augment data handling skillsdata handling skills

Averages Averages Mean Mean Median Median ModeMode

Calculating averages Use temperature readings to calculate Use temperature readings to calculate

the sessionthe session Mean tempMean temp Median tempMedian temp Mode tempMode temp

Are there any differences?Are there any differences? Why?Why?

When would you use each type of When would you use each type of “average”?“average”? Why? Why?

Presenting “averages”

Where have you seen averages Where have you seen averages displayed?displayed?

What about “box & whisker” What about “box & whisker” graphs?graphs? Sats scoresSats scores Good for illustrating spread, Good for illustrating spread,

range and concentration of range and concentration of scoresscores

Directed task Over the hols use a mathematics subject knowledge book (eg Over the hols use a mathematics subject knowledge book (eg

Haylock) to develop an awareness of the different kinds of Haylock) to develop an awareness of the different kinds of discrete and continuous data there are.discrete and continuous data there are. Discrete dataDiscrete data

Unordered discrete data (Categories with no sense of order)Unordered discrete data (Categories with no sense of order) Ordered discrete data (Data values have clear sense of Ordered discrete data (Data values have clear sense of

order)order) Grouped discrete data (Discrete data grouped to make Grouped discrete data (Discrete data grouped to make

process manageable)process manageable) Continuous dataContinuous data

Pseudo continuous data (Results of measurement for Pseudo continuous data (Results of measurement for discrete values)discrete values)

““Real” continuous data (Results from measurements and Real” continuous data (Results from measurements and every possible value has a meaning)every possible value has a meaning)