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The Law of Statistical Regularity says that
- a)Sample drawn from the population under discussion possesses the characteristics of the population
- b)A large sample drawn at random from the population would posses the characteristics of the population
- c)A large sample drawn at random from the population would possess the characteristics of the population on an average
- d)An optimum level of efficiency can be attained at a minimum cost.
Correct answer is option 'C'. Can you explain this answer?
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The Law of Statistical Regularity says thata)Sample drawn from the pop...
The Law of Statistical Regularity states that a large sample drawn at random from a population would possess the characteristics of the population on an average. Let's break down this answer to understand it in detail:
1. Definition of the Law of Statistical Regularity:
The Law of Statistical Regularity is a fundamental principle in statistics that suggests that a large sample, when drawn at random from a population, will exhibit similar characteristics as the entire population on average. This law is based on the assumption that random sampling provides a representative sample of the population.
2. Significance of Random Sampling:
Random sampling is a technique used to select a subset of individuals from a larger population. This process ensures that each member of the population has an equal chance of being included in the sample. By using random sampling, statisticians aim to minimize bias and ensure the sample is representative of the population as a whole.
3. Characteristics of the Population:
The characteristics of a population can refer to various attributes, such as demographics, behaviors, preferences, or any measurable variable of interest. For example, if we want to study the average income of a population, the characteristics would include the income levels of all individuals in that population.
4. Sample Possessing Characteristics of the Population:
According to the Law of Statistical Regularity, a large sample drawn at random from a population will possess the characteristics of the population on an average. This means that the sample will exhibit similar patterns, averages, or distributions as the entire population. However, it is important to note that individual samples may still show some variation or deviation from the population.
5. Importance of Large Sample Size:
The law emphasizes the importance of having a large sample size to increase the reliability of the findings. A larger sample size reduces the margin of error and provides a more accurate representation of the population. With a small sample size, there is a higher chance of sampling error, which can lead to misleading conclusions.
In conclusion, the Law of Statistical Regularity states that a large sample drawn at random from a population will, on average, possess the characteristics of the population. This principle highlights the importance of random sampling and the need for a sufficiently large sample size to obtain reliable statistical results.
1. Definition of the Law of Statistical Regularity:
The Law of Statistical Regularity is a fundamental principle in statistics that suggests that a large sample, when drawn at random from a population, will exhibit similar characteristics as the entire population on average. This law is based on the assumption that random sampling provides a representative sample of the population.
2. Significance of Random Sampling:
Random sampling is a technique used to select a subset of individuals from a larger population. This process ensures that each member of the population has an equal chance of being included in the sample. By using random sampling, statisticians aim to minimize bias and ensure the sample is representative of the population as a whole.
3. Characteristics of the Population:
The characteristics of a population can refer to various attributes, such as demographics, behaviors, preferences, or any measurable variable of interest. For example, if we want to study the average income of a population, the characteristics would include the income levels of all individuals in that population.
4. Sample Possessing Characteristics of the Population:
According to the Law of Statistical Regularity, a large sample drawn at random from a population will possess the characteristics of the population on an average. This means that the sample will exhibit similar patterns, averages, or distributions as the entire population. However, it is important to note that individual samples may still show some variation or deviation from the population.
5. Importance of Large Sample Size:
The law emphasizes the importance of having a large sample size to increase the reliability of the findings. A larger sample size reduces the margin of error and provides a more accurate representation of the population. With a small sample size, there is a higher chance of sampling error, which can lead to misleading conclusions.
In conclusion, the Law of Statistical Regularity states that a large sample drawn at random from a population will, on average, possess the characteristics of the population. This principle highlights the importance of random sampling and the need for a sufficiently large sample size to obtain reliable statistical results.
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The Law of Statistical Regularity says thata)Sample drawn from the population under discussion possesses the characteristics of the populationb)A large sample drawn at random from the population would posses the characteristics of the populationc)A large sample drawn at random from the population would possess the characteristics of the population on an averaged)An optimum level of efficiency can be attained at a minimum cost.Correct answer is option 'C'. Can you explain this answer?
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