data
- information collected from each object in a study
population
- the set of all individuals you are interested in studying
individual
- one object from the population of interest
sample
- the smaller group of objects from the population that we actually collect data for
descriptive statistics
- stating facts about or making graphs with the collected data
inferential statistics
- using sample results along with probabilities to make educated guesses about the
population
parameter
- numerical summary of a population
statistic
- numerical summary of a sample
Example: We typically summarize qualitative data with the percentage of objects in
some category of interest. We typically summarize quantitative data with the average of
the numbers collected.
variable
- the measurement or observation recorded for each individual
qualitative variable
- information collected that places objects into categories
Some examples: eye color, hair color, gender, ethnicity
quantitative variable
- numerical information collected that counts or measures something for each object
Some examples: height, weight, number of absences
quantitative-discrete variable
- numerical information that counts how many
Some examples: number of credit cards you have, number of siblings you have
quantitative-continuous variable
- numerical information that measures how much
Some examples: height, weight, temperature, speed
observational study
- A study where someone measures the value of the response variable without
attempting to influence the value of either the response or explanatory variable. The
researcher simply observes; the researcher does not control the values of either
variables.
designed experiment
- A study where a researcher assigns the individuals in a study to a certain group,
intentionally changes the value of the explanatory variable, and then records the value
of the response variable for each group.
conclusion from an observational study
- There is (or is not) an association between the explanatory variable and the response
variable. For example, there is an association between the increased study time and
increased test scores.
conclusion from a designed experiment
- Changing the value of the explanatory variable causes a change in the response
variable. For example, studying more hours causes a higher test score.
simple random sampling
- choosing a sample in such a way that every sample of size n has the same chance of
being chosen from a population of N objects.
How can you pick a simple random sample using your calculator if you have a
numbered list of objects in the population?
- Use randInt(1,N,2n) and then take the first n distinct numbers and then use the
numbered list to see what objects these numbers correspond to.
stratified sampling
- Sampling where the population is divided into subgroups and a random sample is
taken from each subgroup to be included in the sample. (Taking some from all
subgroups)
systematic sampling
- Sampling where the objects are somehow ordered and then you start with a randomly
chosen object and then take every kth object thereafter.
cluster sampling
- Sampling where the population is divided into subgroups and whole subgroups are
randomly selected to be included in the sample. (Taking all from some subgroups)
convenience sampling
- Sampling done where the objects are easy to obtain. "Hey you" sampling.
sampling error
- The natural tendency for samples to be different from each other and different from the
population from which they were taken.
What is the symbol for sample size?
-n
What is the symbol for population size?
-N
Give an example of a qualitative variable that has numeric values.
- Harper ID number, SSN, jersey number, phone number, etc.
census
- a study where information is collected from every individual in the population