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Sampling procedures It is the way the researcher selects the elements to be investigated in the research study ? Population: Pop. Is the entire set of elements (people, events, behaviors, substances) that could possibly be considered for the study. 1. Identify the pop. From which the sample will be drawn. 2. Pop. Is identified to some extent in the problem & purpose statements & research subproblems. 3. The study pop. is referred to as the target pop. ? The findings are generalized to the target pop. ? Generalization are expected to describe the sample & the target pop. Element The individual units of a pop. are called elements. It can be person, event, behavior. When elements are persons, they referred to as subjects. Sampling criteria Criteria are standards or rules used to make judgments they are rules sets up by the researcher to determine What elements will be included in the pop. & sample. They are characteristics of the elements. Sampling Means selecting a group of elements from the total pop. Which will be studied in the research. It defines the process of making the selections. It has impact on the meaning of the findings. Sample Group of elements selected from the total pop. To conduct the study. Randomization The sample should be randomly selected from the target pop. With each individual in the having equal opportunity to be selected for the sample. This referred to as (randomization) to ensure that the sample is representative of the target pop. Sampling frame The process of identifying each person in the pop. To accomplish this: A list of every member of the target pop. must be acquired. Using the sample criteria to define membership. This listing is referred to as the sampling frame. A sample could be large if the target pop. Was national or international. Accessible pop. Random selection is something ideal, because there is some difficulties of time & cost. For that reason the researcher should define the accessible pop. An accessible pop. Is the portion of the target to which the researcher has reasonable access. It might be within a state, city, nursing unit. Then the sample is obtained form the accessible pop. Findings are generalized first to the accessible pop. & then to the target pop. Representativeness It is important & means that the sample must be like the pop. In as many ways as possible. It must be representative in relation to the variables being examined in the study & other factors. Advantages of sampling Researchers work with samples rather than with pop. Because it is more economical & efficient to work with a small group of elements than with an entire set of elements. ? It does not take time ? Less resources ? Possible to obtain a reasonably, accurate understanding of the phenomena of the study by securing information from a sample. Disadvantages of sampling The data obtained from samples can lead to wrong conclusions. It is difficult to carry out the study without bias. Bias refers to the systematic overrepresentation or underrepresentation of some segment of the pop. In terms of characteristics relevant to the research question. Finding 100 subjects is not difficult. But how much those 100 represent a pop. Example: to carry out a study of student nurses who have engaged in weekly, physical exercise for a period of two years, the researcher need to identify those nurses & select 100 from them. Simply we can not select. Biases in sample selection may be conscious or unconscious. If the researcher decides not to include some of the eligible subjects because they live far away, the sample will be biased. Approaches to sampling A sampling approach is developed to increase representativeness, decrease bias & sampling error. Two types of plan: 1. Probability sampling. It refers to the fact that every member of the population has a probability higher than zero of being selected for the sample. It refers also to as random sampling. It is the matter that every subject has a chance to be represented in the sample. It is not decided by the researcher whom to take & whom to leave. Or may removing them because they do not agree with them. Or do not like them. To obtain probability the researcher must know every element in the pop. Developing a sampling frame, randomly selecting the sample from the sampling frame. For probability 3 designs are discussed: a. Simple random sample: it is the most basic of the probability sampling plans. Elements are selected at random from the sampling frame. This can be done by the imagination of the researcher. If sampling frame is small, names can be written, placed in a container, mixed well & then drawn out one at a time until the desired sample size has been reached. If sample is large elements may already have assigned numbers. For example: numbers are assigned to medical records. Numbers then are selected randomly to obtain a sample. There are many ways of achieving random selection. Using the computer Or the most common method is a table of random numbers. Pencil or the finger is placed on the table with the eyes closed. Then moving up, down, right or left. Using the numbers in order until the desired sample size is obtained. b. Stratified random sampling: it is a variation of simple random sampling in which the population is first divided into two or more strata or subgroups. Used when the researcher find it difficult to achieve the representativeness. Example of that variables age, gender, socioeconomic status. The sample will be divided into groups using the identified variables for example all females. The researcher must have good knowledge of the population to select the parameters by which to stratify. 2. Nonprobability sampling In Nonprobability sampling, not every element of the population has an opportunity for selection in the sample. There is no sampling frame. No clearly identified pop. A hypothetical pop. Is defined. Assumes that the presence of a pop. that cannot be identified by traditional means. For example: individuals who successfully lose weight All the criteria of loosing the weight is unknown. Types of Nonprobability sampling designs 1. Accidental sampling: sometimes called convenience sampling or incidental sampling. Subjects are included because they happened to be in the right place at the right time. Available subjects are simply entered into the study until the desired sample size is reached. Multiple biases may be in action in the sample. Biases present include subjects who are different because they have chosen to enter a treatment program. There are many strategies for selecting an accidental sample. A class room of students, subjects who attend support group, every fifth person who enters the emergency room. Accidental samples are inexpensive, accessible, & usually require less time to acquire. They provide means to conduct studies on topics which cannot be conducted by using probability sampling. Provide means to acquire information in unexplored areas. 2. Quota sampling: uses an accidental sampling procedure with added feature, a strategy to ensure the inclusion of subjects that are underrepresented in the accidental sampling. Women, the aged, the poor, for each study the researcher needs to study the sample for possible underrepresented groups. The goal is to replicate the proportions of subgroups present in the pop. to which the researcher desires to generalize the findings. The quota sampling offers an improvement over accidental sampling & decrease the biases. In most cases in which accidental samples are used, quota sampling could be used & should be used. 3. Purposive sampling: Or judgmental sampling involves the conscious selection by the researcher of certain subjects or elements to include in the study. Examples of good care, poor care. This strategy has been criticized because there is no way to evaluate the precision (exact measurement) of the researcher’s judgment. It is not possible to determine that the pt. element was typical, good, or bad. Sample size The most general rule to decide the sample size is to make the sample as large as possible. Large sample is better approximation of the target pop. than small samples. Factors that must be considered about sample size include the type of study, the number of variables, the sensitivity of the measurement tools, the data analysis & the expected effect size.

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أستاذ المادة سلمى كاظم جهاد الابراهيمي       28/11/2018 17:51:15


Sampling procedures
It is the way the researcher selects the elements to be investigated in the research study
? Population:
Pop. Is the entire set of elements (people, events, behaviors, substances) that could possibly be considered for the study.
1. Identify the pop. From which the sample will be drawn.
2. Pop. Is identified to some extent in the problem & purpose statements & research subproblems.
3. The study pop. is referred to as the target pop.
? The findings are generalized to the target pop.
? Generalization are expected to describe the sample & the target pop.
Element
The individual units of a pop. are called elements. It can be person, event, behavior. When elements are persons, they referred to as subjects.
Sampling criteria
Criteria are standards or rules used to make judgments they are rules sets up by the researcher to determine
What elements will be included in the pop. & sample. They are characteristics of the elements.
Sampling
Means selecting a group of elements from the total pop. Which will be studied in the research. It defines the process of making the selections. It has impact on the meaning of the findings.
Sample
Group of elements selected from the total pop. To conduct the study.
Randomization
The sample should be randomly selected from the target pop. With each individual in the having equal
opportunity to be selected for the sample. This referred to as (randomization) to ensure that the sample is representative of the target pop.
Sampling frame
The process of identifying each person in the pop. To accomplish this:
A list of every member of the target pop. must be acquired. Using the sample criteria to define membership.
This listing is referred to as the sampling frame.
A sample could be large if the target pop. Was national or international.

Accessible pop.
Random selection is something ideal, because there is some difficulties of time & cost.
For that reason the researcher should define the accessible pop.
An accessible pop. Is the portion of the target to which the researcher has reasonable access.
It might be within a state, city, nursing unit. Then the sample is obtained form the accessible pop.
Findings are generalized first to the accessible pop. & then to the target pop.
Representativeness
It is important & means that the sample must be like the pop. In as many ways as possible.
It must be representative in relation to the variables being examined in the study & other factors.
Advantages of sampling
Researchers work with samples rather than with pop.
Because it is more economical & efficient to work with a small group of elements than with an entire set of elements.
? It does not take time
? Less resources
? Possible to obtain a reasonably, accurate understanding of the phenomena of the study by securing information from a sample.
Disadvantages of sampling
The data obtained from samples can lead to wrong conclusions.
It is difficult to carry out the study without bias.
Bias refers to the systematic overrepresentation or underrepresentation of some segment of the pop. In terms of characteristics relevant to the research question.
Finding 100 subjects is not difficult.
But how much those 100 represent a pop.
Example: to carry out a study of student nurses who have engaged in weekly, physical exercise for a period of two years, the researcher need to identify those nurses & select 100 from them.
Simply we can not select.
Biases in sample selection may be conscious or unconscious.
If the researcher decides not to include some of the eligible subjects because they live far away, the sample will be biased.
Approaches to sampling
A sampling approach is developed to increase representativeness, decrease bias & sampling error. Two types of plan:
1. Probability sampling.
It refers to the fact that every member of the population has a probability higher than zero of being selected for the sample.
It refers also to as random sampling.
It is the matter that every subject has a chance to be represented in the sample.
It is not decided by the researcher whom to take & whom to leave.
Or may removing them because they do not agree with them. Or do not like them.
To obtain probability the researcher must know every element in the pop.
Developing a sampling frame, randomly selecting the sample from the sampling frame.
For probability 3 designs are discussed:
a. Simple random sample: it is the most basic of the probability sampling plans.
Elements are selected at random from the sampling frame.
This can be done by the imagination of the researcher.
If sampling frame is small, names can be written, placed in a container, mixed well & then drawn out one at a time until the desired sample size has been reached.
If sample is large elements may already have assigned numbers.
For example: numbers are assigned to medical records.
Numbers then are selected randomly to obtain a sample.
There are many ways of achieving random selection.
Using the computer
Or the most common method is a table of random numbers.
Pencil or the finger is placed on the table with the eyes closed. Then moving up, down, right or left.
Using the numbers in order until the desired sample size is obtained.
b. Stratified random sampling: it is a variation of simple random sampling in which the population is first divided into two or more strata or subgroups.
Used when the researcher find it difficult to achieve the representativeness.
Example of that variables age, gender, socioeconomic status.
The sample will be divided into groups using the identified variables for example all females.
The researcher must have good knowledge of the population to select the parameters by which to stratify.
2. Nonprobability sampling
In Nonprobability sampling, not every element of the population has an opportunity for selection in the sample. There is no sampling frame.
No clearly identified pop.
A hypothetical pop. Is defined.
Assumes that the presence of a pop. that cannot be identified by traditional means.
For example: individuals who successfully lose weight
All the criteria of loosing the weight is unknown.
Types of Nonprobability sampling designs
1. Accidental sampling: sometimes called convenience sampling or incidental sampling.
Subjects are included because they happened to be in the right place at the right time.
Available subjects are simply entered into the study until the desired sample size is reached.
Multiple biases may be in action in the sample.
Biases present include subjects who are different because they have chosen to enter a treatment program.
There are many strategies for selecting an accidental sample.
A class room of students, subjects who attend support group, every fifth person who enters the emergency room.
Accidental samples are inexpensive, accessible, & usually require less time to acquire.
They provide means to conduct studies on topics which cannot be conducted by using probability sampling.
Provide means to acquire information in unexplored areas.
2. Quota sampling: uses an accidental sampling procedure with added feature, a strategy to ensure the inclusion of subjects that are underrepresented in the accidental sampling.
Women, the aged, the poor, for each study the researcher needs to study the sample for possible underrepresented groups.
The goal is to replicate the proportions of subgroups present in the pop. to which the researcher desires to generalize the findings.
The quota sampling offers an improvement over accidental sampling & decrease the biases.
In most cases in which accidental samples are used, quota sampling could be used & should be used.
3. Purposive sampling:
Or judgmental sampling involves the conscious selection by the researcher of certain subjects or elements to include in the study.
Examples of good care, poor care.
This strategy has been criticized because there is no way to evaluate the precision (exact measurement) of the researcher’s judgment.
It is not possible to determine that the pt. element was typical, good, or bad.

Sample size
The most general rule to decide the sample size is to make the sample as large as possible.
Large sample is better approximation of the target pop. than small samples.
Factors that must be considered about sample size include the type of study, the number of variables, the sensitivity of the measurement tools, the data analysis & the expected effect size.


It is the way the researcher selects the elements to be investigated in the research study
? Population:
Pop. Is the entire set of elements (people, events, behaviors, substances) that could possibly be considered for the study.
1. Identify the pop. From which the sample will be drawn.
2. Pop. Is identified to some extent in the problem & purpose statements & research subproblems.
3. The study pop. is referred to as the target pop.
? The findings are generalized to the target pop.
? Generalization are expected to describe the sample & the target pop.
Element
The individual units of a pop. are called elements. It can be person, event, behavior. When elements are persons, they referred to as subjects.
Sampling criteria
Criteria are standards or rules used to make judgments they are rules sets up by the researcher to determine
What elements will be included in the pop. & sample. They are characteristics of the elements.
Sampling
Means selecting a group of elements from the total pop. Which will be studied in the research. It defines the process of making the selections. It has impact on the meaning of the findings.
Sample
Group of elements selected from the total pop. To conduct the study.
Randomization
The sample should be randomly selected from the target pop. With each individual in the having equal
opportunity to be selected for the sample. This referred to as (randomization) to ensure that the sample is representative of the target pop.
Sampling frame
The process of identifying each person in the pop. To accomplish this:
A list of every member of the target pop. must be acquired. Using the sample criteria to define membership.
This listing is referred to as the sampling frame.
A sample could be large if the target pop. Was national or international.

Accessible pop.
Random selection is something ideal, because there is some difficulties of time & cost.
For that reason the researcher should define the accessible pop.
An accessible pop. Is the portion of the target to which the researcher has reasonable access.
It might be within a state, city, nursing unit. Then the sample is obtained form the accessible pop.
Findings are generalized first to the accessible pop. & then to the target pop.
Representativeness
It is important & means that the sample must be like the pop. In as many ways as possible.
It must be representative in relation to the variables being examined in the study & other factors.
Advantages of sampling
Researchers work with samples rather than with pop.
Because it is more economical & efficient to work with a small group of elements than with an entire set of elements.
? It does not take time
? Less resources
? Possible to obtain a reasonably, accurate understanding of the phenomena of the study by securing information from a sample.
Disadvantages of sampling
The data obtained from samples can lead to wrong conclusions.
It is difficult to carry out the study without bias.
Bias refers to the systematic overrepresentation or underrepresentation of some segment of the pop. In terms of characteristics relevant to the research question.
Finding 100 subjects is not difficult.
But how much those 100 represent a pop.
Example: to carry out a study of student nurses who have engaged in weekly, physical exercise for a period of two years, the researcher need to identify those nurses & select 100 from them.
Simply we can not select.
Biases in sample selection may be conscious or unconscious.
If the researcher decides not to include some of the eligible subjects because they live far away, the sample will be biased.
Approaches to sampling
A sampling approach is developed to increase representativeness, decrease bias & sampling error. Two types of plan:
1. Probability sampling.
It refers to the fact that every member of the population has a probability higher than zero of being selected for the sample.
It refers also to as random sampling.
It is the matter that every subject has a chance to be represented in the sample.
It is not decided by the researcher whom to take & whom to leave.
Or may removing them because they do not agree with them. Or do not like them.
To obtain probability the researcher must know every element in the pop.
Developing a sampling frame, randomly selecting the sample from the sampling frame.
For probability 3 designs are discussed:
a. Simple random sample: it is the most basic of the probability sampling plans.
Elements are selected at random from the sampling frame.
This can be done by the imagination of the researcher.
If sampling frame is small, names can be written, placed in a container, mixed well & then drawn out one at a time until the desired sample size has been reached.
If sample is large elements may already have assigned numbers.
For example: numbers are assigned to medical records.
Numbers then are selected randomly to obtain a sample.
There are many ways of achieving random selection.
Using the computer
Or the most common method is a table of random numbers.
Pencil or the finger is placed on the table with the eyes closed. Then moving up, down, right or left.
Using the numbers in order until the desired sample size is obtained.
b. Stratified random sampling: it is a variation of simple random sampling in which the population is first divided into two or more strata or subgroups.
Used when the researcher find it difficult to achieve the representativeness.
Example of that variables age, gender, socioeconomic status.
The sample will be divided into groups using the identified variables for example all females.
The researcher must have good knowledge of the population to select the parameters by which to stratify.
2. Nonprobability sampling
In Nonprobability sampling, not every element of the population has an opportunity for selection in the sample. There is no sampling frame.
No clearly identified pop.
A hypothetical pop. Is defined.
Assumes that the presence of a pop. that cannot be identified by traditional means.
For example: individuals who successfully lose weight
All the criteria of loosing the weight is unknown.
Types of Nonprobability sampling designs
1. Accidental sampling: sometimes called convenience sampling or incidental sampling.
Subjects are included because they happened to be in the right place at the right time.
Available subjects are simply entered into the study until the desired sample size is reached.
Multiple biases may be in action in the sample.
Biases present include subjects who are different because they have chosen to enter a treatment program.
There are many strategies for selecting an accidental sample.
A class room of students, subjects who attend support group, every fifth person who enters the emergency room.
Accidental samples are inexpensive, accessible, & usually require less time to acquire.
They provide means to conduct studies on topics which cannot be conducted by using probability sampling.
Provide means to acquire information in unexplored areas.
2. Quota sampling: uses an accidental sampling procedure with added feature, a strategy to ensure the inclusion of subjects that are underrepresented in the accidental sampling.
Women, the aged, the poor, for each study the researcher needs to study the sample for possible underrepresented groups.
The goal is to replicate the proportions of subgroups present in the pop. to which the researcher desires to generalize the findings.
The quota sampling offers an improvement over accidental sampling & decrease the biases.
In most cases in which accidental samples are used, quota sampling could be used & should be used.
3. Purposive sampling:
Or judgmental sampling involves the conscious selection by the researcher of certain subjects or elements to include in the study.
Examples of good care, poor care.
This strategy has been criticized because there is no way to evaluate the precision (exact measurement) of the researcher’s judgment.
It is not possible to determine that the pt. element was typical, good, or bad.

Sample size
The most general rule to decide the sample size is to make the sample as large as possible.
Large sample is better approximation of the target pop. than small samples.
Factors that must be considered about sample size include the type of study, the number of variables, the sensitivity of the measurement tools, the data analysis & the expected effect size.


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