Statistical Studies
A population is the group that is being studied by the research
A sample is any subset of the population
Example: A principal gives the students in her school a survey to fill out. The entire
school is the population. One classroom of students would be a sample.
A parameter describes a population
A statistic describes a sample
Example: 47% of students in a school respond they are satisfied with the school lunch
options. This is a parameter because it measures the entire population of students.
Meanwhile, 36% of the students in Mr. Potter’s class responded that they are satisfied
with the school lunch options. This is a statistic because it measures a sample on the
students.
Quantitative variables measure an amount of something (can be discrete or
continuous)
o Discrete variables are finite values (counting values)
o Continuous variables can be any amount (measured amounts)
Qualitative variables describe a type of something (usually can be thought of as a
name or word description)
Example: On a survey given to a patient at a hospital, it asks for height, body weight,
regular physician’s name, and how many times they have visited their physician in the
last year. Determine what type of variables each of those are.
1. Height is a continuous variable
2. Body weight is a continuous variable
3. Physician’s name is a qualitative variable
4. Number of times visiting physician is a discrete variable
The response variable is the variable of interest
The explanatory variable is the variable that explains or has an effect on the
response variable
Example: A researcher wants to determine how the weight of a car affects gas mileage.
The variable of interest is the gas mileage, so that is our response variable. The weight of
the car explains the gas mileage, so weight is the explanatory variable.
