Presentation Secondary School Listowel

Teaching & Learning Plan

Strand 1 Teaching & Learning PlanClass Plan

• Introduction to Statistics & Data Handling• Questionnaire• Examine Types of Data• Tally selected data from collated data• Recap on familiar methods of presenting data• Histograms with equal & unequal class intervals• Stemplots• Significance testing for comparing 2 sets of data

Types of data

Categorical

Nominal Ordinal

Numeric

Discrete Continuous

C

Categorical Data: The answer to “what colour is your hair?” produces categorical data, which fits into the categories “black”, “brown”, “red”, “blonde”, “other”.•Nominal e.g. naming or classifying e.g. blue eyes, brown eyes, blood group types, makes of car, gender, favourite subject/sport, pets. These data cannot be organized according to any ‘natural’ order.•Ordinal – involves some order e.g. first, second, third, Jan, Feb., March, schoolwork pressure – a lot, some, very little, none.

Categorical

NominalCan be identified by particular names or categories, and cannot be organized according to any natural order.

Examples Suitable graphical representation

Gender : female or maleHair colour: black, blonde etcFavourite sport: soccer, rugby etc

Bar Chart, Pictogram, Pie Chart

OrdinalIdentified by categories which can be ordered in some way

Watching TV: never, rarely, sometimes , a lot

Bar Chart, Pictogram, Pie Chart

Numeric Data: Data represented by real numbers

Discrete – distinct values, e.g. how many people live in each household i.e. cannot have 2.75 people in a household

Continuous – infinite number of values between any 2 given values e.g. heights, weights, lengths in the long jump, high jump.

Numeric

Discrete Examples Suitable graphical representation

Data can only have a finite number of values

Number of peas in a pod,Age in years (as opposed to age)

Bar Chart, pie chart, line graph, stemplot

ContinuousData can assume an infinite number of values between any 2 given values. Students height may be 1.4325m

Height, arm span, foot length.

Histogram, line graph, stemplot

In practice no scale is truly continuous because measurement is restricted by some level of accuracy.

Pie Chart

17

16

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Bar Chart

1 2 30

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35

40

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Trend Graph

January February March April May June July0

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40Car Sales

Dublin Sales

Donegal Sales

Pictogram

• Brid: • Aisling:• Padraic:• Colm:

• Key : represents 4 books

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Histogram

Height / cm

freq

uenc

y

150 155 160 165 170 175 180 185

Height cm 150-154 155-159 160-164 165-169 170-174 175-179 180-185

Frequency 2 3 12 16 18 5 4

150-154 155-159 160-164 165-169 170-174 175-179 180-1850

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4

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Histogram

Height / cm

freq

uenc

y

Height cm 150-154 155-159 160-164 165-169 170-174 175-179 180-185

Frequency 2 3 12 16 18 5 4

Areas Of Rectangles Key =1

Area =18 Area =18 Area =18

Area =12 Area =12 Area =12

Key =1

0

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Histogram

Height / cm

Fre

quen

y De

nsity

150 155 160 165 170 175 180 185

Height / cm

Height /cm 150 -159 160-164 165-169 170-174 175-184

Frequency 5 12 16 18 9

14

15

16

17

18

19

7 7 9

0 0 2 2 2 2 3 4 5 5 5 6 7

0 1 1 1 2 2 3 4 5 7

0 1 2

8

Original Data ( Sample of 30)

160, 162, 170, 171, 175, 172, 165, 171, 164, 177, 171, 160, 172, 162, 159, 173, 157, 166, 165, 174, 181, 165, 168, 162, 182, 167, 157, 162, 163, 180.

Ordered Data

157, 157, 159, 160, 160, 162, 162, 162, 162, 163, 164, 165, 165, 165, 166, 167, 168, 170, 171, 171, 171, 172, 172, 173, 174, 175, 177, 180, 181, 182.

N = 30 ( Sample Size) Height in cm.

18 2 = 182 Key/ Legend

14

15

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17

18

19

7 7 9

0 0 2 2 2 2 3 4 5 5 5 6 7

0 1 1 1 2 2 3 4 5 7

0 1 2

8

Rotating a Stemplot gives a Histogram.

14

15

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165

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150, 154, 154, 155, 157, 159, 160, 160, 160, 161, 161, 162, 162, 162, 163,163, 164, 164, 165, 165, 166, 166, 167, 167, 168, 169, 170, 170, 173, 177.

Canadian Girls ( Sample of 30) Ordered. Height in cm

Back to Back Stemplot.

18 2 = 182 Key/ Legend

7 7 9

0 0 2 2 2 2 3 4

0 1 1 1 2 2 3 4 5 7

0 1 2

5 5 5 6 7 8

Sample A. Irish girls

2 2 1 1 1 0 0 0

4 4 09 7 5

23344

6 5 57 7 69 8

3 0 07

Sample B. Canadian girls

Word Bank

Statistics Data categories Histogram Range

Data Numeric discrete Frequency density Dispersion

Sample space Numeric continuous Stemplot/ stem & leaf

diagram

Clusters

Questionnaire Categorical nominal Significant/ Levels of

significance

outliers

Fair test Categorical ordinal median

Tally/Frequency Class intervals: Equal or

unequal