1.2
Nominal
Data at the nominal level of measurement are qualitative only. Data at this level are categorized using names, labels, or qualities. No mathematical computations can be made at this level. Ex: numbers on soccer jersey
Simple Random Sample
every possible sample of the same size has the same chance of being selected.
Sampling
.1. Count or measure of PART of population 2. Information less complete 3. Less expensive 4. Common in statistical studies 5. Sample MUST be representative, or data will be biased
The 4 Levels of Measurement
1. Nominal Level 2. Ordinal Level 3. Interval Level 4. Ratio Level
convience sample
1. Worst type of sampling 2. Often leads to biased results 3. Chooses members of population that are easy to get to only members of the population that are easy to get are sampled.
Quantitative Data
Numerical measurements or counts
Random Sample
One where every member of a population has an equal chance of being selected
Ordinal
qualitative or quantitative. Data at this level can be arranged in order, or ranked, but differences between data entries are not meaningful.
What is the difference between a random sample and a simple random sample?
With a random sample, each individual has the same chance of being selected. With a simple random sample, all samples of the same size have the same chance of being selected.
Census
is a count or measure of an entire population. Taking a census provides complete information, but it is often difficult and costly to perform.
Stratified Sample
members of the population are divided into two or more subsets, called strata. A sample is then randomly selected from each of the strata. This ensures that members of each group within the population will be sampled.
Qualitative Data
Attributes, labels, or non-numerical entries
Sampling error
Difference between results of a sample and those of the population
Select all the levels of measurement for which data can be quantitative.
Interval Ratio Ordinal
Observational study (aka "Natural Experiment")
Researcher observes and records, but does not influence the responses Ex: Observing mating habits of buffalo
Experiment
a treatment is applied to PART of a population and responses are observed. The researcher in an experiment deliberately influences the responses.
three examples of data sets that have inherent zeros
age, precipitation, speed
Interval
quantitative only. Data at this level can be ordered and differences between data entries are meaningful, but a zero entry is not an inherent zero. ex) dates, temperature
Cluster Sample
the population is divided into subgroups, called clusters, and all of the members of one or more (but not all) clusters are selected.
Name each level of measurement for which data can be qualitative.
nominal and ordinal
Systematic Sample
each member of the population is assigned a number. The members of the population are ordered in some way, a starting number is randomly selected, and then sample members are selected at regular intervals from the starting number.
Placebo
is a fake treatment used in experiments. To minimize the possibility of the subjects reacting favorably to a placebo, the subjects will typically be blinded as to whether they are receiving a real treatment or the placebo.
What is an inherent zero?
is a reference point used to describe data sets which are indicative of magnitude of an absolute or relative nature. a zero that implies none.
Ratio
quantitative only. Data at this level are similar to data at the interval level, with the added property that a zero entry is an inherent zero. ex) percents, height,age