Population - Answers the entire group of individuals or subjects about which the research wants
information about
Parameter - Answers a specific characteristic of the population that the researcher wants to determine
and make statements
μ: mean of the population
η: median of the population
σ: standard deviation of population
σ²: variance of the population
π: proportion of successes in the population
ρ: the correlation between two variables in a population
hypothesis - Answers a statement about a population parameter
a conjecture as to what one thinks the parameter value would be
ex. μ= mean
sample - Answers a subset of the population
goal is to have the sample be representative of the population, the characteristics of the population that
are important are mimicked in the sample
statistic - Answers a descriptive measure computed or determined from data in a sample
generally match the identified parameters of interest
ex. if the parameter is mean, then the statistic is mean
n: the number of subjects in the sample
X̄: mean of the sample
M: median of the sample
s: standard deviation of the sample
s²: variance of the sample
p̂ : proportion of successes in a sample
r: sample correlation between two variables
,parameter vs statistic - Answers parameter: summarize data from a population
statistic: summarize data from a sample
inference - Answers a statement about a population parameter based on statistics computed from data
in a sample
2 types: estimation and statistical tests
estimation inference - Answers use the sample data to compute a statistic to compute a confidence
interval that provides a statement about the population parameter
statistical test inference - Answers make a hypothesis about parameter and use the sample data to test
whether or not the hypothesis is logical or not
descriptive statistics - Answers branches statistics concerned with numerical and graphical techniques
for describing characteristics of a population and for comparing characteristics among populations
inferential statistics - Answers use data and statistics computed from a sample to make inferences
(statements) about a population
replication/repetition - Answers experiments or samples that have repeated measurements made
(similar to repeated trials to ensure the data is accurate)
constant - Answers - characteristic whose measurements are the same for every observation in the
population or sample
- the measurements do not change in repeated trials over time
ex. the population is: all years, and the characteristic is the number of days in January each year
variable - Answers characteristic whose measurements vary from trial to trial or individual to individual
*when given a variable:
1. figure out if it's qualitative or quantitative
2. if quantitative, see if it's discrete or continuous
qualitative/categorical variable - Answers - the measurements vary from subject to subject, but NOT in
degree
- the measurements can NOT be arranged in order of magnitude
*parameter of interest usually involves a proportion
ex. asking what state students are born in or the gender of each person
, quantitative variable - Answers - measurements vary in magnitude from subject to subject, ranking can
be applied
*parameter of interest usually involves a mean
ex. number of students in each class or the height of each student -> some are taller than others, so
there can be an order
discrete quantitative variable - Answers variable whose measurements can assume only a countable
number of possible values
ex. number of students in a class, number of votes received by a political candidate
continuous quantitative variable - Answers variable whose measurements can assume any one of
countless number of values
- a measurable quantity (height, weight, time, speed)
- calculated (rates, averages, proportions, percentages)
ex. heights of the students (measured)
ex. percentage of students at the university (calculated)
simple random sample - Answers - used when the population size is NOT known
- uses a table of random digits
- using the number of digits of the population size, assign each person a number with those amount of
digits from 1 to the population size
- looking at the table choose the range of numbers that fit with the assigned numbers for the population
to get the sample
pros and cons of simple random sampling - Answers pros:
- easy to select if the population size is known
- the most commonly used
cons:
- it does NOT guarantee a representative sample
- it may over represent or under represent
stratified random samples - Answers - the population is divided into 2 or more groups of similar subjects
(strata)