Chap%206%20Hair - Chapter 6 Descriptive and Causal Research...

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Chapter 6: Descriptive and Causal Research Designs
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Relationship of Research Types Problem Exploratory Research Possible Causes Probable Causes Descriptive Research Causal Research
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Descriptive Research (separate outline for experimental research) Types Advantages/Disadvantages Total Survey Error Sampling Error Nonsampling Error Nonresponse error Response error
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Descriptive Research Most Common Type is Survey Research, i.e., asking questions (other forms are observational, e.g., scanner, internet tracking data – addressed last chapter ) Purpose To describe the characteristics of a population, count the frequency with which something occurs (e.g., frequencies distribution) To assess the relationship between variables (e.g., crosstabs, correlations) To make specific predictions (e.g., regression)
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Types of Survey Research Methods Person- administered Telephone- administered Self- administered
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Usage Rates for Survey Methods Internet 36.8% CATI 25.3% Hybrid 12.0% Face-to-face intercepts 11.5% Mail 3.3% Other 4.1%
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Descriptive Research Types Advantages/Disadvantages Total Survey Error Sampling Error Nonsampling Error Nonresponse error Response error
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Advantages/Disadvantages of Survey Research Design Advantages Accommodates large sample sizes (if needed) Generalizable to target population (can be) Easy to administer and record answers Facilitates advanced statistical analysis Disadvantages Questions that accurately measure variables can be difficult to develop In-depth data difficult to obtain Low response rates
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ALL SURVEYS CONTAIN ERROR!!!
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Descriptive Research Types Advantages/Disadvantages Total Survey Error Sampling Error Nonsampling Error Nonresponse error Response error
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Total Survey Error reflects the difference between the population's true mean value (an unknown) on the characteristic of interest and the mean observed value obtained from a sample of respondents Total Survey Error = random sampling error (not a “mistake” as stated on p. 105) + nonsampling error (which may be random or nonrandom, i.e., systematic)
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Total Survey Error When generalizing to Operational Population Total Survey Error = Sampling Error (Random) + Nonsampling Error (Random and Nonrandom ) Population μ Sampling error Nonsampling error Sample X T _ X o _ X T _ = “true” sample mean X o _ = Observed (measured) sample mean For example, if a population mean income was $22,000 and we selected a sample that had a true income of $23,600, yet we measured it as $24,100, then the total survey error would equal $2,100 ($1600 due to sampling error and $500 due to nonsampling error).
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Operational Population (Sampling Frame Error) μ Sampling error Nonsampling error Sample X T _ X o _ X T _ = “true” sample mean X o _ = Observed (measured) sample mean For example, if a population mean income was $22,000 and we selected a sample that had a true income of $23,600, yet we measured it as $24,100, then the total survey error would equal $2,100 ($1600 due to sampling error and $500 due to nonsampling error).
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