Chapter 1: Introduction to (1-1 ∼ 1-3)

1-1: An Overview of Statistics

Statistics is a science. Statistics is a collection of methods.

(1) Planning (2) Obtaining from a small part of a large group. (3) Organizing (4) Summarizing (5) Presenting (6) Analyzing (7) Interpreting (8) Drawing conclusions

Statistics has two fields. : consists of procedures used to summarize and describe the impor- tant characteristics of a set of . Inferential statistics: consists of procedures used to make inferences about population characteristics from contained in a drawn from this population.

Studying about ⇒ Population Population is a complete collection of all measurements or data that are being considered. is the collection of data from every member of a population. Parameter: A numerical describing some characteristic of a population.

We are going to use the information contained in ⇒ Sample Sample is a subcollection of members selected from a population. : A numerical measurement describing some characteristic of a sample.

1-2 : Data Classification

Data: Collections of observational studies and . Data is a set of measurements, or responses, ... Obtaining data: Data must be collected in an appropriate way.

Simple Random Sample (SRS) of n subjects is selected in such a way that every possible sample of the same size n has the same chance of being chosen. Two types of data. (1) Quantitative Data: measures a numerical quantity or amount. (a) Discrete Data: a finite or countable number of values. (b) Continuous Data: the infinitely many values corresponding to the points on a line interval.

(2) Qualitative Data: measures a quality or characteristic.

Another way of classifying data. (1) Nominal : Categories only. Data cannot be arranged in an ordering scheme. (2) Ordinal level of measurement: Categories are ordered, but differences can’t be found or are meaningless. (3) Interval level of measurement: Differences are meaningful, but there is no zero starting point and ratios are meaningless. (4) Ratio level of measurement: Ratios are meaningful, and there is a natural zero starting.

1-3 : Data Collection and Experimental Design ( method)

Two sources: : Observing and measuring specific characteristics without attempting to modify the subjects being studied. Experiment: Apply some treatment and then observe its effects on the subjects.

Sampling techniques :

Simple Random Sample:

Random Sampling: Each member of the population has an equal chance of being selected.

Stratified Sampling: Subdivide the population into at least two different subgroups so that subjects within the same subgroup share the same characteristics.

Cluster Sampling: Divide the population into sections, then randomly select some of those clusters, and then choose all members from those selected clusters.

Systematic Sampling: Select some starting point, then select every k th element in the population.

Convenience Sampling: Use results that are easy to get.

Multistage Sampling: Collect data by using some combination of the basic sampling methods.