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**Research Methods in Crime and Justice**

Chapter 8 Sampling

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Sampling Sampling is a scientific technique that allows a researcher to learn something about a population by studying a few members, or a sample of that population. There are numerous types of sampling. Some sampling techniques allow researchers to predict something about a population. Other sampling techniques merely provide researchers insight into a population.

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Sampling Sampling allows researchers to learn a great deal about a population without having to solicit information from every member of that population. Without sampling, researchers would not have the time or money to study and learn about large populations. Making Research Real 8.1 – Low Morale at the Jail (p. 160) A county sheriff uses a probability sampling technique (simple random sampling) to determine the cause of low morale among the employees in a jail. Because the jail is a large urban jail it was not possible for the sheriff to interview every employee.

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Sampling Basics Scientifically, sampling is based on the central limit theorem. Proposes that numerous samples from a population will produce about the same result. The results from these samples (when plotted on a graph, will be normally distributed (i.e. cluster around the middle).

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Sampling Basics A population is the entire set of individuals or groups that is relevant to a research project. A census collects information from an entire population. A sample collects information from a group within that population.

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Sampling Basics The terms members, cases and elements are used interchangeably to describe the individual components of a population or sample. A list of the individual components of a population is referred to as a sampling frame. The exact process used to select the sample is called a sampling plan.

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**Sample Bias and Precision**

Bias is a condition that causes a sample to be unrepresentative of the population from which it came. There are two primary causes. Random sampling error. Selection bias

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**Sample Bias and Precision**

Random sampling error is one form of bias. It represents the difference between the results the researcher gets from the sample and what the results might have been had the entire population been polled. Samples from highly diverse populations tend to have more sampling error.

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**Sample Bias and Precision**

Bias may also be caused by selection. Selection bias is any process that systematically increases or decreases the chances that certain members of a population will be selected into the sample. Ideally, all members of a population should have an equal chance of being selected into the sample.

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**Sample Bias and Precision**

A sample’s level of precision is a measure of a sample’s representativeness to the population from which it came.

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**Sample Bias and Precision**

A sample’s level of precision is determined by; The size of the sample in relation to the size of the population. Larger populations tend to require larger samples. The diversity within the population. Highly diverse populations require larger samples. The frequency at which the social phenomenon of interest occurs within the population. Rare or infrequent phenomenon require larger samples. Making Research Real 8.2 – How Safe is Your Hamburger?(p. 165) A researcher attempts to develop an appropriate sampling plan for measuring the pathogenic infestation within the nation’s meat supply. This is an illustration (outside ‘traditional’ criminal justice) of a practical application of sampling. Making Research Real 8.3 – It’s Just a Simple Telephone Survey (p. 166) The students in Professor Jackson’s class attempt to collect a sample residents to interview. The professor notices a bias in the sampling plan that causes older residents to be more likely to be included in the sample. Making Research Real 8.4 – Predicting the Outcome of the Public Bond Election (p. 167) Although not criminal justice per se, a practitioner may be interested in using a sample This case illustrates the function of sampling precision

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**Types of Sampling There are two major types of sampling**

Probability sampling techniques Rely on the random selection of cases Allow researchers to predict what is happening in the population based on what they learn from the sample. Non-Probability sampling techniques Do not rely on the random selection of cases. Do not allow researchers to predict what is happening in the population based on what they learn from the sample.

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Probability Sampling In simple random sampling, a researcher randomly selects cases into a sample directly from a population. Each member must have an equal and non-zero chance of being selected into the sample.

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Probability Sampling In systematic random sampling, a researcher uses a structured process to randomly select cases into a sample. The researcher might select every tenth case from the population.

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Probability Sampling In cluster sampling (a form of multi-stage sampling), researchers identify natural groupings (i.e., clusters) within the population. Some of these natural groupings are randomly selected in the initial stage of the sampling process. Cases are then randomly selected from the chosen clusters until an appropriate sized sample has been collected. Making Research Real 8.5 – A Survey of Probationers (p. 170) This story illustrates the use of a cluster sampling technique to overcome the lack of a comprehensive (statewide) list of probationers. The researcher randomly selects individual probation departments and then selects probationers from each of these departments.

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Probability Sampling In stratified random sampling (a form of multi-stage sampling) , researchers create groupings within the population. From each of these groupings (i.e. strata) the researcher will randomly select cases until an appropriate sized sample is collected. Making Research Real 8.6 – Measuring Binge Drinking (p. 172) This story illustrates the use of a stratified sampling technique to insure that the sample includes (proportionately) all grade levels (freshmen, sophomores, juniors, seniors and graduate students). The strata are the grade levels and a random sample of cases were selected from each strata.

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**Non-Probability Sampling**

Although prediction from the sample to the population is not possible, non-probability sampling techniques offer clear advantages. Allows researchers to take advantage of a long term association with of research subjects. A definitive list of the population (sampling frame) may not be available. Allows researchers to study distinctive or generally inaccessible research subjects.

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**Non-Probability Sampling**

A convenience sample is created when a researcher selects a sample from a group of people who are at hand or easily available. A convenience sample As the name implies, these members are convenient to or known by the researcher. Also known as an availability sample. Making Research Real 8.7 – What is Life Like for an Undocumented Immigrant? (p. 175) A police chief draws a convenience sample of undocumented immigrants to study how they live and negotiate life without benefit of citizenship. He draws his sample from church membership rolls.

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**Non-Probability Sample**

A snowball sampling relies on the sample members themselves to increase the sample size. After a member of the population is identified the researcher asks the member to identify other members of the population. The researcher contacts these prospective members and repeats the process until the sample produces meaningful results. Making Research Real 8.8 – The Prostitute Study (p. 176) Because there is no definitive list of prostitutes (i.e. a sampling frame) are researcher chooses to collect a non-probability sample. He is interested in them because of an increase in admissions to hospitals of prostitutes overdosing on a new form of illicit narcotic. He uses a snowball sampling technique to find prostitutes to interview and asks them about a new form of drug use among their peers.

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**Non-Probability Sample**

Sometimes a sample can be a single case. Case studies are highly detailed inquiries into or descriptions of a population or phenomenon. There are two types of case samples. Typical case sample Extreme case sample

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**Non-Probability Sample**

A typical case sample involves a single case that exemplifies a common or typical pattern within the population. An extreme case sample involves a single case that is atypical, uncharacteristic or uncommon within the population. Making Research Real 8.9 – What Happened to Sally May? (p. 178) A researcher uses an extreme case study approach to study what happened to a girl who was murdered by her non-custodial parent. This study revealed inconsistencies and lapses in the state’s child welfare system.

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Getting to the Point Sampling is a scientific technique that allows a researcher to learn something about a population by studying only a few members of the population. Sampling is based on a concept called the central limit theorem. The central limit theorem gives us confidence that if we collect a large enough sample, the sample will be representative of the larger population.

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Getting to the Point A population is the entire set of individuals or groups that is relevant to a research project. A census collects information from an entire population.

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Getting to the Point The terms members, cases and elements are used interchangeably to describe the individual components of a population or sample. A list of the individual components of a population is referred to as a sampling frame. The exact process used to select the sample is called a sampling plan.

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**Getting to the Point Random sampling error is one form of bias.**

It represents the difference between the results the researcher gets from the sample and what the results might have been had the entire population been polled. Samples from highly diverse populations tend to have more sampling error.

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**Getting to the Point Selection bias is another form of bias.**

It is caused by any process that systematically increases or decreases the chances that a member of a population will be selected into the sample.

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Getting to the Point A sample’s representativeness of a population is referred to as its level of precision. The level of precision is influenced by the size of the population; the amount of variability within the population, and the frequency with which relevant social phenomena occurs.

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Getting to the Point Probability sampling is a general type of sampling that relies on random selection. Random selection means that each member of a population has an equal and non-zero chance of being selected into the sample.

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Getting to the Point In simple random sampling, a researcher randomly selects cases into a sample directly from a population, similar to drawing names out of a hat. In systematic random sampling, a researcher uses a structured process to randomly select cases into a sample. For example, the researcher might select every tenth case from the population.

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Getting to the Point In cluster sampling, researchers identify natural groupings (i.e., clusters) that exist within the population. Some of these natural groupings are randomly selected in the initial stage of the sampling process. Cases are then randomly selected from the chosen clusters until an appropriate sized sample has been reached.

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Getting to the Point Stratified random sampling is a multi-stage probability sampling technique that involves randomly selecting cases from groups created within the population. These groups, called strata, are defined by the researcher. This form of probability sampling helps researchers insure the sample will be representative of the overall population.

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Getting to the Point Non-probability sampling techniques do not rely on random selection and therefore do not allow a researcher to use the sample to predict what might be happening in the larger population. Even so, non-probability samples can provide in-depth information on a population that might not otherwise be accessible and/or information that can be used to develop theories about various phenomena.

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Getting to the Point Convenience samples, also known as availability samples, are created when a researcher selects a sample from a group of people who are at hand or easily available. Normally, researchers rely upon their own experience and judgment when creating a convenience sample.

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Getting to the Point Snowball sampling is a non-probability sampling technique that relies on the sample members themselves to increase the sample size. Members recruited into the sample identify other members of the population and refer the researcher to these contacts until the sample ‘snowballs’ in size.

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Getting to the Point Typical and extreme case samples consist of a single member of a population . In a typical case sample, a researcher uses a case study to illustrate a common or typical pattern. In an extreme case sample, a researcher uses a case study to illustrate an uncommon or atypical pattern.

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**Research Methods in Crime and Justice**

Chapter 8 Sampling

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