Presentation Secondary School Listowel Teaching & Learning Plan

Strand 1 Teaching & Learning Plan Class 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 Nominal Can be identified by particular names or categories, and cannot be organized according to any natural order. Examples Suitable graphical representation Gender : female or male Hair colour: black, blonde etc Favourite sport: soccer, rugby etc Bar Chart, Pictogram, Pie Chart Ordinal Identified 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 Continuous Data can assume an infinite number of values between any 2 given values. Students height may be m 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

Bar Chart

Trend Graph

Pictogram Brid: Aisling: Padraic: Colm: Key : represents 4 books

Height cm Frequency

Height cm Frequency

Areas Of Rectangles Key =1

Area =18 Area =12 Key =1

Height /cm Frequency

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. 182= 182 Key/ Legend

Rotating a Stemplot gives a Histogram.

, 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. 182= 182 Key/ Legend Sample A. Irish girls Sample B. Canadian girls

Word Bank StatisticsData categoriesHistogramRange Data Numeric discreteFrequency densityDispersion Sample spaceNumeric continuous Stemplot/ stem & leaf diagram Clusters QuestionnaireCategorical nominal Significant/ Levels of significance outliers Fair testCategorical ordinal median Tally/FrequencyClass intervals: Equal or unequal