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Chapter 1 Getting Started What is Statistics?. Individuals vs. Variables Individuals People or objects included in the study Variables Characteristic.

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Presentation on theme: "Chapter 1 Getting Started What is Statistics?. Individuals vs. Variables Individuals People or objects included in the study Variables Characteristic."— Presentation transcript:

1 Chapter 1 Getting Started What is Statistics?

2 Individuals vs. Variables Individuals People or objects included in the study Variables Characteristic of the individual to be measured or observed

3 Quantitative vs. Qualitative Quantitative Variables Have value or numerical measurement for which operations such as addition or averaging make sense Qualitative Variables Describes an individual by placing the individual into a category or group, such as male or female

4 Population vs. Sample Population Data Data is from every individual of interest Population Parameters are numerical measures that describe an aspect of a population Sample Data The data are from only some of the individuals of interest Sample Statistics are numerical measures that describe an aspect of a sample

5 Levels of Measurement Nominal – Names, Labels, Categories Ordinal – Arranged in meaningful mathematical order Interval – Differences are meaningful Ratio – Division or percentage comparisons make sense; zero point

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7 Chapter 1 Getting Started 1.2 Random Samples

8 Simple Random Sample (SRS) A simple random sample of no measurements from a population is a subset of the population selected in such a manner that every sample of size n from the population has an equal chance of being selected.

9 Random Number Tables (RNT) Used to help secure a SRS Steps: – Number all members of the population sequentially. – Drop a pin on the RNT to pick a starting point – Pull digits n at a time, discarding non-used numbers – Repetition?

10 Other Methods to Secure a SRS Systematic Stratified Cluster Multistage Convenience

11 Systematic Sampling Population is numbered Select a starting point at random and pick every kth member

12 Stratified Sampling Divide population into distinct subgroups based on specific characteristics Draw random samples from each strata

13 Cluster Sampling Divide population into pre-existing segments or clusters (often geographic). Make a random selection of clusters. All members of cluster are chosen.

14 Multistage Sampling Use a variety of sampling methods to create successively smaller groups at each stage. Final sample is made of clusters.

15 Convenience Sampling Create sample by selecting population members which are easily available


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