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