STATISTICS - PowerPoint Presentation

Slide1

STATISTICSfSlide2
Slide3

Some vocab Statistics

is the

art of solving problems and answering questions by collecting and analysing data.

Data

are

the facts or information we collect and analyze. (plural)(note datum is the singular term)Data set- a list of unorganized data. Often called the raw dataSlide4

More vocabPopulation- a collection of individuals about which we want to draw info/ conclusions

Sample- a subset of the population. (important for a sample to be random

and to avoid

bias

!)

Survey- a collection of info from a

sampleParameter- a numerical quantity measuring some aspect of a population (i.e. mean (average) and usually have greek letters like αβγδμσρ etc)Distribution- the “spread” of the dataOutliers- much larger or smaller than general body of data. Slide5

Raw Data.....just the numbersSlide6

Statistical InvestigationStep 1: Examining a problem which might be solved using data and asking questions (how many students ride bikes to school)

Step 2: Collecting the dataStep 3: Organising the data.

Step 4: Summarising and displaying the data.

Step 5: Analysing the data, and making a conclusion

Step 6: Writing a report (presenting your findings)Slide7

Census/Sample A census

is a method which involves collecting data about EVERY individual in a whole

population.

A

sample

is a method which involves collecting data about a

part of the population.Not as detailed or accurate as census, but easier.Slide8

Problems with a sample

A sample can be biased if the data has been unfairly influedned in the collection

p

rocess. A biased sample won’t represent the whole population

Question

: Are you good at climbing trees?Slide9

Other problemsQuestion: Do Americans

like cheese burgers???I am American.

I like cheese burgers.

There fore ALL Americans like cheeseburgers.

Valid argument?!?!

…..i

think NOT!A sample must be sufficiently large to represent the whole populationSlide10

Variables in StatisticsCategorical variable

– describes qualities or characteristics. Can be divided into categories.

The information is called categorical data.

Examples.

Getting to school: Bus, train, bike, car, walking.

Color of eyes: Slide11

Variables in statistics Quantitative

variable- has a numerical value, and is often called a numerical variable.

The information collected is

called

numerical

data.Can be discrete or continuous.A quantitative discrete variable takes exact number values. (Think counting)Examples. Number of people in a house holdThe score out of 30 on a testThe number of sunny days in Stavanger. 1,2,3,4,.....Slide12

Variables in StatisticsA

quantitative continuous variable takes numerical values within a certian CONTINOUS range. (think measuring)

Examples.

The weights of new born babies

The heights of 9th grade students

TimeSlide13

Bar Chart vs. Histogram

Histogram

DISCRETE DATA

Continuous DataSlide14

Bar Chart and HistogramBoth have:

Frequency on vertical axis and scores on horizontalColumn widths are EQUAL

Modal class = highest barSlide15

Presenting the DataSee text page 378/9Slide16

Presenting and Interpreting DataSlide17

Presenting and Interpreting DataSlide18
Slide19
Slide20
Slide21

The Distribution of Data(going to lunch)Slide22
Slide23
Slide24

The “spread” of the DataSlide25

OutliersSlide26
Slide27
Slide28
Slide29

Interesting Statisticshttp://www.worldometers.info/

http://www.informationisbeautiful.net/visualizations/

http://www.babynamewizard.com/voyager#ms=false&exact=false

http://news.bbc.co.uk/2/hi/science/nature/7137462.stmSlide30

See “big” data pdf