Some vocab Statistics is the art of solving problems and answering questions by collecting and...

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STATISTICSF

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 data

More vocab

Population- 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 sample Parameter- 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 data Outliers- much larger or smaller than general body of

data.

Raw Data

.....just the numbers

Statistical Investigation

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

Step 2: Collecting the data Step 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)

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.

Problems with a sample

A sample can be biased if the data has been unfairly influedned in the collection process. A biased sample won’t represent the whole population

Question: Are you good at climbing trees?

Other problems

Question: 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 population

Variables in Statistics

Categorical 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:

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 hold The score out of 30 on a test The number of sunny days in Stavanger. 1,2,3,4,.....

Variables in Statistics

A 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 Time

Bar Chart vs. Histogram

Histogram

DISCRETE DATAContinuous Data

Bar Chart and Histogram

Both have: Frequency on vertical axis and scores

on horizontal Column widths are EQUAL Modal class = highest bar

Presenting the Data

See text page 378/9

Presenting and Interpreting Data

Presenting and Interpreting Data

The Distribution of Data

(going to lunch)

The “spread” of the Data

Outliers

See “big” data pdf