Chapter 1-3 review
Data is the information we gather with experiments and with surveys.
Ex: Say we want to know how well a group of students did in a statistics course. The data could
be what every student made on their final exam grades.
3 Statistical Methods
Design: planning how to obtain data. Ex: conduct an experiment/survey
Description: summarizing the raw data and presenting it in a useful format. Ex: charts,
graphs, average (mean), median, etc.
Inference: making decisions or predictions based on data
Subjects are the entities that we measure in a study.
Ex: people, schools, rats, etc.
Population vs. Sample
Population: all subjects of interest
Sample: subset of the population for whom we have data
Ex: Let’s say we want to know how many Texas Tech students like coffee. To figure this out we
surveyed 50 random students in the S.U.B.
Population: every Texas Tech Student
Sample: the 50 random students we surveyed
Parameter vs. Statistic
Parameter: numerical summary of the population, usually unknown
Statistic: numerical summary of a sample taken from the population
Ex: The average number of cigarettes smoked by all teenagers last year -------- parameter
The average number of cigarettes smoked by a proportion of teenagers last year ------ statistic
The proportion of all teenagers who smoked in the last month ------ parameter
The proportion of teenagers who smoked last month out of 50 teenagers ------ statistic
After looking at the cars in the North Commuter parking lot we conclude that 67% of the
people who park in North Commuter drive trucks -------- 67% is a parameter
A survey of 50 car lots in America found that 35% of the cars in the car lots in America are
BMWs --------- 35% is a statistic
Randomness: each subject in the population has the same chance of being included in the
sample (Random sampling enables the sample to be a good reflection of the population)
Ex: Let’s say I want to know if I want to know if everyone in the class understands a question
The top 10 scorers on the first exam ------ not random
Everyone sitting in the last row ------- not random
Picking 10 names off the attendance ------ random
Variability
Note that measurements may vary from subject to subject and from sample to sample.
Ex: If I want to know how the class did on an exam. If I took the average of everyone whose
name starts with an ‘s’, the average will be different than if I take the average of everyone whose
name starts with a ‘m’.
In saying this, we can get a more accurate idea of the population if we take larger samples.
Computer and Statistics
Data file: large sets of data are typically organized in a spreadsheet format
Database: an existing archive collection of data files
Applet: short application program for performing a specific task. Ex: random number generator
