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Learning Objectives

Learning Objectives. To understand the difference between the population and the sample To understand how to select a sample from the population How to avoid bias in the investigation To understand the overall strategy of the statistical enquiry Data Collection and Data Cleaning.

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Learning Objectives

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  1. Learning Objectives • To understand the difference between the population and the sample • To understand how to select a sample from the population • How to avoid bias in the investigation • To understand the overall strategy of the statistical enquiry • Data Collection and Data Cleaning

  2. Understanding the difference between a population and a sample

  3. Population v Sample • A population is a group of objects that have something in common. • The term often refers to a group of people, as in the following examples. • E.g. All students at NZ High Schools • All citizens of NZ • All the Trout in the Rivers of Taranaki • All the road accidents recorded in 2012

  4. Population v Sample • A sample is a small cross section of objects drawn from the total population which will be analysed in order to make inferences about the population. • What must the investigator guarantee about the sample?

  5. Population v Sample • A sample is a small cross section of objects drawn from the total population which will be analysed in order to make inferences about the population. • What must the investigator guarantee about the sample? • Randomly chosen individuals/object • Large enough sample must be chosen (>30 per subgroup) • Equal numbers of individuals/objects in each subgroup

  6. Data Cleaning • Check that all data values are recorded correctly in the right place on the table • Check that all units on all data values are consistent. As long as the same units are used then the data values can be combined • Be suspicious of data values that seem out of place • Check all zero entries. Are they truly zero or did it mean no data was avaialable

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