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Questions and Answers
What is a sample in the context of research?
What is a sample in the context of research?
What is one primary reason for using sampling in research?
What is one primary reason for using sampling in research?
Which term refers to an entire group of elements with common characteristics?
Which term refers to an entire group of elements with common characteristics?
Which sampling method allows every individual in the population an equal chance of being selected?
Which sampling method allows every individual in the population an equal chance of being selected?
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What is sample bias?
What is sample bias?
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When might researchers decide to sample the entire population?
When might researchers decide to sample the entire population?
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Which of the following is a characteristic of a sample?
Which of the following is a characteristic of a sample?
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What is a major drawback of relying solely on samples for conclusions?
What is a major drawback of relying solely on samples for conclusions?
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What is the first step in the sampling process?
What is the first step in the sampling process?
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Which sampling method relies on subjective considerations for selection?
Which sampling method relies on subjective considerations for selection?
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What characterizes probability sampling?
What characterizes probability sampling?
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Which of the following is an example of convenience sampling?
Which of the following is an example of convenience sampling?
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What is quota sampling based on?
What is quota sampling based on?
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Which sampling technique is especially useful for reaching hard-to-reach populations?
Which sampling technique is especially useful for reaching hard-to-reach populations?
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What aspect of sampling greatly influences generalizability?
What aspect of sampling greatly influences generalizability?
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Why is non-probability sampling generally less preferred?
Why is non-probability sampling generally less preferred?
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What impact does a smaller margin of error have on sample size requirements?
What impact does a smaller margin of error have on sample size requirements?
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Which confidence level requires a larger sample size?
Which confidence level requires a larger sample size?
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Which sampling method ensures every member has an equal chance of being selected?
Which sampling method ensures every member has an equal chance of being selected?
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In the sample size calculation formula, what does the letter 'Z' represent?
In the sample size calculation formula, what does the letter 'Z' represent?
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What is a major cause of sampling error in research?
What is a major cause of sampling error in research?
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What is the estimated sample size needed when aiming for a confidence level of 95% and a margin of error of 5% with an estimated response rate of 50%?
What is the estimated sample size needed when aiming for a confidence level of 95% and a margin of error of 5% with an estimated response rate of 50%?
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In stratified sampling, what is the primary purpose of dividing the population into subgroups?
In stratified sampling, what is the primary purpose of dividing the population into subgroups?
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Which sampling method is being used when patients are divided by age and randomly selected from each group?
Which sampling method is being used when patients are divided by age and randomly selected from each group?
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What type of sampling method is demonstrated when surveys are handed out to customers visiting in a specific period?
What type of sampling method is demonstrated when surveys are handed out to customers visiting in a specific period?
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How does larger sample size impact accuracy in research?
How does larger sample size impact accuracy in research?
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What sampling method selects every nth member from a list?
What sampling method selects every nth member from a list?
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In a clinical trial selecting patients using similar medications for over six months, what sampling method is likely being used?
In a clinical trial selecting patients using similar medications for over six months, what sampling method is likely being used?
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Why is sample size important in statistical tests?
Why is sample size important in statistical tests?
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What describes the sampling method when 100 patients are randomly selected from a hospital's patient list?
What describes the sampling method when 100 patients are randomly selected from a hospital's patient list?
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What defines sampling error?
What defines sampling error?
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What is the effect of larger sample sizes on confidence intervals?
What is the effect of larger sample sizes on confidence intervals?
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Study Notes
Introduction to Sampling in Pharmacy Research
- A sample is a subset of the population
- Samples are used for statistical testing when a population is too large
Why We Use Sampling
- Saves time and resources
- Improves accuracy
Sampling the Entire Population
- When the population is very small
- When there are unlimited resources
- When a high response rate is expected
- A census is an example
Steps in the Sampling Process
- Identify the target population
- Identify the accessible population
- Determine the size of the sample needed
- Select the sampling technique
- Implement the plan
Non-Probability Sampling Methods
- Selecting sampling units based on subjective considerations, such as personal judgment or convenience
- Less preferred to probability sampling
- Potential bias
- Less representative of the target population
- Most commonly used
Convenience Sampling
- Choosing individuals who are easiest to access
- Example: Sampling patients who visit a specific pharmacy during a week to study customer satisfaction
Purposive Sampling
- Selecting individuals based on specific characteristics relevant to the research
- Example: Choosing patients who have been using a medication for at least six months to assess long-term effects
Quota Sampling
- Selecting a sample based on predefined characteristics of the population
- It has subgroups which can be pre-determined: gender (male/female), occupational status.
- Example: A researcher employs quota sampling to study medication adherence in a pharmacy, selecting 100 patients to match population proportions of age (40% 18-50, 60% over 50) and condition (60% hypertension, 40% diabetes).
Snowball Sampling
- Sampling technique where participants recruit other participants for a study, particularly useful for hard-to-reach populations
- Example: A researcher studies medication use among undocumented immigrants by initially recruiting participants through community health centers, then asking these participants to refer others.
Probability (Random) Sampling
- All members of the population have an equal chance of selection
- The best method, but more expensive, and likely to be representative of the relevant population
- Using a method such as a dice, coins, hat or random number tables to select randomly from the list the number of members required for the sample.
Simple Random Sampling
- Each member of the population has an equal chance of being selected
- Applicable when the population is small, homogeneous & readily available
- Example: Randomly selecting patients from a list to test a new drug.
Stratified Sampling
- The population is divided into subgroups (strata) and random samples are taken from each
- Example: Dividing patients by age group to ensure equal representation in a clinical trial.
Systematic Sampling
- General procedure is to select every 5th or 6th participant from the population
- If the population elements are in random order, it is very representative of random sampling
- Example: Choosing every 10th student from a list of 1,000 after starting at a randomly selected position.
Sampling Error
- Sampling error arises due to the natural variability in the population, and the fact that samples are smaller than the entire population
- It occurs because a sample is only a subset of the entire population, and thus it may not perfectly represent the whole.
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Causes:
- Sample size: Smaller samples are more prone to larger sampling errors.
- Population Heterogeneity: More diverse populations may lead to greater sampling error.
Sample Size
- It refers to the number of observations or data points included in a sample drawn from a population.
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Importance of sample size:
- Accuracy: Larger sample sizes generally lead to more accurate estimates of population parameters.
- Statistical Power: A bigger sample improves the ability to detect a true effect or difference when one exists.
- Confidence Intervals: Larger samples yield narrower confidence intervals, providing a more precise range for the population parameter.
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Factors Influencing Sample Size:
- Population Size: The total number of individuals in the population can impact the required sample size.
- Margin of Error: A smaller margin of error requires a larger sample size.
- Confidence Level: Higher confidence levels (e.g., 95% vs. 90%) necessitate larger samples.
- Variability: More variability in the population increases the required sample size to achieve reliable results.
Sample Size Calculation
- The formula for calculating sample size (for estimating a proportion) is: n=
- where:
- n = required sample size.
- Z= Z-score (confidence level).
- p = Estimated proportion of the population
- E = Margin of error
- Example of Sample Size Calculation:
- Imagine you are studying the effect of a new vaccine and want to determine how many people you need in your sample to ensure the results are accurate. You want to be 95% confident that your results are correct, and you want the margin of error to be no more than 5%. You estimate that 50% of people will respond well to the vaccine.
- Using the following information, calculate how many people you need in your study:
- Z = 1.96 (this corresponds to a 95% confidence level),
- E = 0.05 (the margin of error is 5%).
- The answer is 385.
Identifying Sampling Methods
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- Stratified Sampling: The researcher divides patients into two groups based on age and then randomly selects 50 patients from each group.
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- Convenience Sampling: The pharmacy conducts a study to evaluate customer satisfaction by handing out surveys to patients who visit the pharmacy during the first week of each month.
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- Purposive Sampling: Only patients who have been using similar medications for more than six months are selected for the study.
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- Simple Random Sampling: The researcher randomly selects 100 patients from a list of all patients in the hospital.
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Description
This quiz delves into the fundamental concepts of sampling as it applies to pharmacy research. Learn about the importance of sampling, various methods, and the steps involved in the sampling process. It covers both probability and non-probability sampling techniques, emphasizing their relevance in research accuracy and resource management.
