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28 Cards in this Set
- Front
- Back
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Population mis-specification error
Frame error Non-response error Questionnaire design error Question wording (response) error Data coding & entry error |
types of non sampling errors
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refers to how close the survey findings are to the true population values.
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accuracy of sample
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Simple Random
Systematic Random Cluster |
Random (probability) sample
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Judgement
Snowball Quota Convenience |
Non-Random (non-probability) sample
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Sample methods that use random sampling are termed --------- sampling methods.
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probability
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Several clusters may be selected using the --------------
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two-step area sample.
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Used when it is anticipated that different groups within the population will answer the research question differently.
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stratified sampling
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Decision makers want fast, relatively inexpensive answers… nonprobability samples are------- ----- ------- -----than probability samples.
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faster and less costly
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are errors in the research process pertaining to anything except the sample size.
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non sampling errors
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Fieldworker errors
Intentional Unintentional Respondent Intentional Unintentional |
types of non sampling errors
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Multiple submissions
Bogus respondents and responses Population misrepresentation |
types of data collection erros with online surveys
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three types of non response error?
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refusal, break off, item omission
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refers to the creation of a computer file that holds the raw data taken from all of the completed questionnaires.
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data entry
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is defined as a matrix of numbers and other representations that includes all of the relevant answers of all the respondents in a survey.
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a data set
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is defined as the process of describing a data set by computing a small number of measures that characterize the data set in ways that are meaningful to the client.
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data analysis
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four functions of data analysis
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It summarizes the data.
It generalizes sample findings to the population. It compares for meaningful differences. It relates underlying patterns. |
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Determines the Appropriate Types of Data Analysis
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the research objective
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when summarizing your findings what two objectives
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Describing the typical response (“central tendency”)
How typical are respondents (“variability”) |
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As long as we take a representative sample (probability), we have the tools to generalize the findings in the sample data to the total population.
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concept of generalization
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is a computed value based on sample data.
These values may be either a percentage, average, or other analysis value. |
sample finding
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is defined as the true value when a census of the population is taken and the “true” value is determined using all members of the population.
It is rare that the population fact is ever known. Sample findings, however, are used to estimate population facts. Sample findings are our best estimates of population facts though they always contain sample error. |
A population fact:
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strength of evidence in order to be more confident about generalization is based on
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the sample size (the larger the sample size, the greater the evidence.
the variance within the sample data (the less the variance in the sample data, the stronger the evidence.) |
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is defined as the process of generalizing a sample’s finding to the population.
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paramater estimation
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(“yes,” ordered Egg McMuffin; “no,” did not order Egg McMuffin)
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data are categorical. it is proper to calculate percentages when doing categorical
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If you took many, many samples, and plotted the sample percentage, p, for all these samples as a frequency distribution, it would approximate a ---------------called the sampling distribution.
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a bell shaped curve
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When using a categorical scale (groups) the type of central tendency is -------- and the variability is -------- or -----------
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mode, frequency or distribution
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when using a metric scale (indicates amount) the central tendency is ----- and the variability is -------- or ---------
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average, range or std. deviation
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is a measure of the variability in the sampling distribution based on what is theoretically believed to occur were we to take a multitude of independent samples from the same population.
The shape of the sampling distribution is a function of variability and sample size. |
standard error
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