Types of Sampling In applications: Probability Sampling: Simple Random Sampling‚ Stratified Random Sampling‚ Multi-Stage Sampling * What is each and how is it done? * How do we decide which to use? * How do we analyze the results differently depending on the type of sampling? Non-probability Sampling: Why don’t we use non-probability sampling schemes? Two reasons: * We can’t use the mathematics of probability to analyze the results. * In general‚ we can’t count on a non-probability
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There are many ways to select a random sample. Four of them are discussed below: Simple Random Sampling: In this sampling technique‚ each sample of the same size has the same probability of being selected. Such a sample is called a simple random sample. One way to select a simple random sample is by a lottery or drawing. For example‚ if we need to select 5 students from a class of 50‚ we write each of the 50 names on a separate piece of paper. Then‚ we place all 50 names in a hat and mix them thoroughly
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R. Rapid Surveys (unpublished)‚ © 2008. NOT FOR COMMERCIAL DISTRIBUTION 3 Simple Random Sampling 3.1 INTRODUCTION Everyone mentions simple random sampling‚ but few use this method for population-based surveys. Rapid surveys are no exception‚ since they too use a more complex sampling scheme. So why should we be concerned with simple random sampling? The main reason is to learn the theory of sampling. Simple random sampling is the basic selection process of sampling and is easiest to understand
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statistics‚ a sample is a subset of a population. Typically‚ the population is very large‚ making a census or a complete enumeration of all the values in the population impractical or impossible. The sample represents a subset of manageable size. Samples are collected and statistics are calculated from the samples so that one can make inferences or extrapolations from the sample to the population. This process of collecting information from a sample is referred to as sampling. A complete sample is a set
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I. Sample Size Calculation (Calculated by Hand Only) Example 9.65 Pg. 297 The Chevrolet dealers of a large county are conducting a study to determine the proportion of car owners in the county who are considering the purchase of a new car within the next year. If the population proportion is believed to be no more than 0.15‚ how many owners must be included in a simple random sample if the dealers want to be 90% confident that the maximum likely error will be no more than 0.02? Given Data π = 0
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Lecture Illustration – Random Digits Table Simple Random Sampling can be conducted by two methods: i) Drawing from Hats ii) Random Digits Table Refer to your Random Digits Table in Appendix. Illustration 1 Suppose we have a population of 30 students from Curtin University Foundation Program: |Allen |Connie |Diaz |Howard |Law |Piper | |Andres |Cowel |Dunst
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group of 12 students‚ we want to select a random sample of 4 students to serve on a university committee. How many different random samples of 4 students can be selected? a.|48| b.|20‚736| c.|16| d.|495| ANS: D 2. Parameters are a.|numerical characteristics of a sample| b.|numerical characteristics of a population| c.|the averages taken from a sample| d.|numerical characteristics of either a sample or a population| ANS: B 3. How many simple random samples of size 3 can be selected from a population
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Lecture Notes on Introductory Statistics‚ I (P.P. Leung) Lecture notes are based on the following textbook: N.A. Weiss (2012)‚ Introductory Statistics‚ 9th edition‚ Pearson. Chapter 1 The Nature of Statistics 統計本質 §1.1 Two kinds of Statistics §1.4 Other Sampling Designs (其他抽樣方法) Chapter 1 The Nature of Statistics 統計本質 What is Statistics? 何謂統計? From Wikipedia‚ the free encyclopaedia: Statistics is a mathematical science pertaining to the collection‚ analysis‚ interpretation
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Research and statistics for managerial decision making Assignment 1 Mohammed Ahmed Ali 0170026 1.1 Four different beverages are sold at a fast food restaurant: soft drinks‚ tea‚ coffee‚ and bottled water. Explain why
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how they differ from each other Steps in carrying out the major probability sample designs The strengths and weaknesses of the various types of probability sampling Differences between stratified sampling and quota sampling Differences between stratified sampling and cluster sampling Differences between multistage cluster sampling and multiphase sampling INTRODUCTION Once a choice is made to use a probability sample design‚ one must choose the type of probability sampling to use. This chapter
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