Chapter 5 Flashcards
What is the purpose of inferential stats
used to learn about the population from a sample
two types of inferential stats
estimation
hypothesis testing
Parameter
mathematical characteristics of populations
A survey was conducted on 500 students from a population of 20,000 students at a university. It found that 74% of students were employed during the semester.
determine the
population
sample
statistic
parameter
population= 20,000 students
sample= 500 selected for interviews
statistic= 74% sample that held a job during the semester
parameter= % of all students in the population who held a job
Statistics
mathematical characteristics of samples
What is a random sample
every case in the population has the same chance of being selected
What is a representative sample
a sample that reproduces important characteristics of the population
What does EPSEM stand for and what does it mean
equal probability of election methods
Every element or case in the population must have an equal probability of being selected
What is a non random sample
lack equal or known probability of selection
sampling frame
the list of elements from which the sample will be selected
Probability sample
a sample selected using a random process so that each element in the population has a known likelihood of being selected
How to select a simple random sample
Number all the elements consecutively starting at 1.
Pick a sample size (n) from the total population (N).
Using a random number table or computer program to generate a list of random numbers.
The sample will be comprised of the cases whose element numbers match the randomly generated numbers.
Sampling distribution
the theoretical probabilistic distribution of a statistic for all possible samples of a given size
three distributions of inferential statics
sample
population
sampling distribution
Example of the concept of sampling distribution
-draw a ample of ten people from a population of 100 multiple times
-calculate the mean age for each of these samples
-each sample will have a different outcome
characteristics of a sampling distribution
-normal in shape
-mean equal to the population mean
-SD equal to the population SD
σ/n.
As n becomes large…
the sampling distribution of a sample mean will approach normality with a mean and SD of σ/n.
If n is to small…
you can’t apply statistics
Importance of Central Limit Theorem
it removes the constraint of normality in the population
What should a sample size generally be
100 or more
The larger the sample size…
the more normal the curve gets
Sampling distribution
distribution of a statistic for all possible outcomes of a certain sample size
mean of the sampling distribution of means =
population mean
standard deviation of sampling distribution=
population standard deviation divided by the square root on n
systematic sample
every “i” the case in the sampling frame is selected
stratified random sample
this type of sampling ensures that subgroups in the population are proportionally represented in the sample
how to select a stratified random sample
divide into subgroups
select a simple random sample or a systematic sample form each stratum
If there are 80 students and 20 staff you wouldn’t choose 5 from each you would take 2 staff and 8 student’s
multistage cluster sampling
select clusters
then select subunits within the cluster
Canadians provinces territories yukon, nunavut sask, alberta
Example of a multi stage cluster sample
select a few provinces
select a random subunit from each
choose a city
choose a street
choose a house
choose someone from the household
3 qualities of a probability sample
representative allows for generalization from a sample to population
inferential statistical tests
sample means can be used to estimate population means
convenience sampling
cases are included because they are readily available
asking only people you see walk down the hallway
snowball sampling
researcher makes contact with some individuals who in turn provide contacts for other participants
Ask an addict a question and he sends you to another addict and they send you to another addict
Quota sampling
collecting a specified number of cases in particular categories to match the proportion of cases in that category in the population
you can learn from it but can’t apply it to the general population
the ______ determines whether the sample is a random sample
selection process
The sales representatives employed by a large pharmaceutical firm are numbered sequentially. From those numbers, a computer program is used to select 30 random numbers. A sample of 30 reps whose numbers correspond to those randomly selected numbers is obtained.
Simple random sample
A sampling method in which one of the first k individuals and then every kth individual thereafter is selected
Systematic random sample
A sampling method in which groups naturally occurring in the population are randomly selected and a subsample of these cases within each selected unit is sampled
Cluster sample
A sampling method in which some cases in the population, because of the way the sample is chosen, will not have a chance of being included in the sample
Non-probability sample
A sampling method in which the population is first divided into a sublist based on a relevant trait, and a simple random sample is then taken from each group
Stratified random sample
Representative
The quality a sample is said to have if it reproduces the major characteristics of the population from which it was drawn
What is a simple, random sample
A method for choosing cases from a population in which every case has an equal chance of being included
Standard error
The standard deviation of a sampling distribution
