2. Lesson 2 – Populations and Samples - definitions
Statistics: Gathering, describing & analysing data. OR numeric description of sample data
Data: Information Gathering
Population: Particular group of interest ex: everybody in a city; everybody in something,
ex: all males or all females, all children between 6-9 ya, ex: everybody in a city; .
Note the word ALL, is all inclusive of a category
Parameter: Numerical description of a population characteristic
Ex: the mean height of all males in the world; IQ of all children in the world, mean IQ of all females in USA, 75% of all kids age
6-9 play games
Note the word NUMERICAL from definition; it is a number
Sample: Subset of the POPULATION from which DATA is collected
Ex: we asked 100 males IN THE CITY what their fav movies
Sample Statistic: Numeric description of particular sample CHARACHTERISTIC
Ex: 100 female asked from city; 47% disliked chocolate
3. Lesson 3 – Descriptive vs Inferential Statistics
Branches of statistics
Descriptive Statistic – gather, sort, summarise data from sample
Inferential statistics – use descriptive statistics (DATA) to ESTIMATE POPULATION PARAMETERS
Problem: Based on a phone survey, 22% of all men dislike football
Inferential as we estimate the percentage of a population from a sample (survey)
PR2: 65% of seniors at a local HS apply to college plan to major in business
Descriptive because
Population
Sample
4. Lesson 4 – Apply Definitions in Statistics
Height of every 4th bottle on an assembly line: Sample
Ages of all USA president: Population
A research stop 100 people in a store to ask a survey of household income
Population: people in a store
Sample: 100 people chosen
Parameters describe populations, statistics describe sample
The average number of hour per week a sample of 10 yo. spend watching TV is 20h
Statistic: 20h/week for the sample
87% of all patients in a hospital report having alcohol problem.
Parameter: describe all patients