0
Add your answer:
Earn +20 pts
Why do smaller populations need larger sample sizes?
They do not. Population size does not affect the sample size. The variability of the characteristic that you are trying to measure and the required accuracy will determine the appropriate sample size.
What is the sample size for a population of 60010?
well a sample size can be any size depending on the requirements. A sample size could be 10 people of that entire population or it could be 1000 people.
What does the Central Limit Theorem say about the traditional sample size that separates a large sample size from a small sample size?
The Central Limit Theorem states that the sampling distribution of the sample means approaches a normal distribution as the sample size gets larger — no matter what the shape of the population distribution. This fact holds especially true for sample sizes over 30.
Does the accuracy of a sample in representing the characteristics of the population from which it was drawn always increase with the size of the sample?
yes the size is 4444
What are the effects of sample size on sampling error?
The sampling error is inversely proportional to the square root of the sample size.
Factors to consider in determining sample size?
Factors that determine sample size
How do you determine the skip interval in systematic sampling?
Assuming that you know the population size, N, and that you are confident that the sample size, n, you have chosen is adequate, then the skip interval is ~n/N. For example, if the populaton size if 998 and you reckon that you need a sample size of 20 then the skip interval would be 50.
Why do smaller populations need larger sample sizes?
They do not. Population size does not affect the sample size. The variability of the characteristic that you are trying to measure and the required accuracy will determine the appropriate sample size.
Factors that determine sample size?
1. population to deal with in the sample 2. Location. ocation where the sample will be done 3. design. how the sample will be taken 4. result. how the outcome will be determined
What is the conclusion of sieve analysis?
The conclusion of a sieve analysis is to determine the particle size distribution of a sample. This is achieved by passing the sample through a series of sieves with decreasing mesh sizes to separate and weigh the particles in different size fractions. The data collected from this analysis can be used to determine the uniformity of the sample and its suitability for various engineering applications.
What can one do with a sample size calculator?
According to the website Survey System's Creative Research Systems page, you can use a sample size calculator to determine how many people need to be interviewed in order to meet your target.
What is absolute sample size?
It is the number of elements in the sample. By contrast, the relative sample size is the absolute sample size divided by the population size.
What difference between Statistical Sampling and non-statistical sampling?
Statistical sampling is an objective approach using probability to make an inference about the population. The method will determine the sample size and the selection criteria of the sample. The reliability or confidence level of this type of sampling relates to the number of times per 100 the sample will represent the larger population. Non-statistical sampling relies on judgment to determine the sampling method,the sample size,and the selection items in the sample.
Why was it important for Mendel to study such a large sample pea plants to determine the probability of inheritance?
Answer D- A higher sample size gives more accurate results- APEX LEARNING
Why was it important to Mendel to study such a large sample of pea plants to determine the probability of inheritance?
Answer D- A higher sample size gives more accurate results- APEX LEARNING
What is the difference between sample and sample size?
a sample is a sample sized piece given... a sample size is the amount given in one sample
Characteristics of a good sample?
1. the sample should be representative thus carefully selected. 2. the sample should be adequate thus significant enough.
