Scientifically valid samples are those that accurately represent the population being studied, ensuring that findings can be generalized. They should be selected using appropriate sampling methods, such as random sampling, to minimize bias. Additionally, sample size must be sufficient to provide reliable and statistically significant results. Valid samples also adhere to ethical standards and maintain the integrity of the research process.
To achieve a scientifically valid sample for your study, ensure that your sample is representative of the population you are investigating. This can be done through random sampling methods, which help eliminate bias and improve generalizability. Additionally, determine an appropriate sample size using statistical power analysis to ensure that your findings are reliable. Finally, consider stratifying your sample to account for key demographic variables that may influence the results.
To ensure a scientifically valid sample for your study, you must first define your target population clearly and use random sampling methods to select participants, minimizing bias. Additionally, the sample size should be sufficiently large to provide statistical power and representativeness. It's also essential to ensure that the sample reflects the diversity of the population in relevant characteristics, such as age, gender, and socioeconomic status, to enhance generalizability of the findings.
a biased sample is valid determin
Because without representative sample, your results will not be valid.
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.
at random to represent the population
Statistically the results will not be scientifically valid if the sample size is too small.
a biased sample is valid determin
observation
If you're talking about what I think you're talking about, the fact that it is not "scientifically valid" might have a lot to do with it.
Many statistical statements for a population which are based on a sample are not valid if the sample is not representative.
1) What conditions are required to form a valid large-sample confidence interval for µ?
Because without representative sample, your results will not be valid.
The temperature of a urine sample should be around 98.6 degrees Fahrenheit (37 degrees Celsius) to be considered valid.
30 min
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.
statistics