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Which sample size out of a population of 1000 is most likely to lead to a valid conclusion?
Providing of course that a sample is representative of the population from which it is drawn, the bigger it is the more likely it will be to lead to a valid conclusion. Therefore, the best sample size when there are no restrictions, as in this case, would be one of 1000.
What are the disadvantages of non probability sampling?
It is quite likely that the sample is not representative of the population and so while statistical conclusion may be valid for the sample, they may not apply to the population.
When a sample is representative of a population is said to be what?
When a sample is representative of a population, it is said to be a "probability sample" or simply a "representative sample." This means that the characteristics of the sample accurately reflect those of the larger population, allowing for valid inferences and generalizations. Such samples are essential in statistical analysis to ensure the findings can be applied to the entire population.
Is a biased sample always valid?
a biased sample is valid determin
If A Population Is A Sample Of The Population Could Be .tion could be .?
If a population is considered a sample of a larger population, it means that the characteristics and behaviors of that sample can be used to make inferences about the entire population. This approach is often employed in statistical analysis where studying the entire population is impractical. The sample should be representative to ensure that the findings are valid and reliable. Proper sampling methods help minimize bias and enhance the accuracy of conclusions drawn about the larger population.
Which sample size out of a population of 1000 is most likely to lead to a valid conclusion?
Providing of course that a sample is representative of the population from which it is drawn, the bigger it is the more likely it will be to lead to a valid conclusion. Therefore, the best sample size when there are no restrictions, as in this case, would be one of 1000.
What are the disadvantages of non probability sampling?
It is quite likely that the sample is not representative of the population and so while statistical conclusion may be valid for the sample, they may not apply to the population.
Which conditions may be met for a scientifically valid sample?
at random to represent the population
Why is obtaining a representative sample important?
Many statistical statements for a population which are based on a sample are not valid if the sample is not representative.
What does it mean to say that the sample variance provides an unbiased estimate of the population variance?
It means you can take a measure of the variance of the sample and expect that result to be consistent for the entire population, and the sample is a valid representation for/of the population and does not influence that measure of the population.
When a sample is representative of a population is said to be what?
When a sample is representative of a population, it is said to be a "probability sample" or simply a "representative sample." This means that the characteristics of the sample accurately reflect those of the larger population, allowing for valid inferences and generalizations. Such samples are essential in statistical analysis to ensure the findings can be applied to the entire population.
Is a biased sample always valid?
a biased sample is valid determin
Is a simple random sample valid?
Yes, a simple random sample is considered valid as it ensures that every member of the population has an equal chance of being selected. This randomness helps eliminate bias and allows for generalizations to be made about the larger population based on the sample. However, the validity of the results also depends on the sample size and the proper execution of the sampling method. Properly conducted, it provides a reliable foundation for statistical inference.
When the sample size is large valid confidence intervals can be established for the population mean irrespective of the shape of the underlying distribution?
Yes, but that begs the question: how large should the sample size be?
The most important step to ensure accuracy in a sample is?
The most important step to ensure accuracy in a sample is random selection. By randomly choosing samples from the population, you minimize bias and increase the likelihood that your sample is representative of the entire population. This helps to draw reliable conclusions and make valid inferences based on the sample data.
A sample of a population should be large enough to?
span the full spectrum of a population's genetic variation.-apexI got you guysssss.feel free to hmu on snap king.youssof ( need knew friends ;--;)
Why would someone want to assume that your sample data represents a population distrubution?
Most people take samples so that they may make estimates of parameters of interest: mean, variance, etc for the whole population. For such an estimate to have any validity the sample data must be assumed to represent a population distribution. Otherwise any conclusions based on the sample are valid only for the sample: hardly worth the effort!
