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

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Chapter 1: Introduction to Statistics (1-1 ∼ 1-3) 1-1: An Overview of Statistics Statistics is a science. Statistics is a collection of methods. (1) Planning (2) Obtaining data 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. Descriptive statistics: consists of procedures used to summarize and describe the impor- tant characteristics of a set of measurements. Inferential statistics: consists of procedures used to make inferences about population characteristics from information contained in a sample drawn from this population. Studying about ) Population Population is a complete collection of all measurements or data that are being considered. Census is the collection of data from every member of a population. Parameter: A numerical measurement 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. Statistic: A numerical measurement describing some characteristic of a sample. 1-2 : Data Classification Data: Collections of observational studies and experiment. Data is a set of measurements, or survey 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 level of measurement: 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 (Sampling method) Two sources: Observational study: 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..

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