statistics
at random to represent the population
N>=30 N at-least greater then 30
The main advantage is that the sample is representative of the population and the mean of the sample is an unbiased estimate of the population mean. Also, characteristics of other statistics based on the sample are well understood. However, sometimes it may not be possible to gather valid information from a sampling unit and then the sample is no longer random. This can be either because the sampling unit cannot be located or has been compromised by external factors. This can be particularly serious if the "missing" units share a common characteristic. Also, simple random samples may not include any units representing characteristics that are rare in the population - but important in the context of the experiment.
The valid prediction range is the range of the "predictor."
Random Sampling increases the reliability and validity of your research findings. To begin with, Reliability: By randomly picking research participants, the likelihood that they are from different backgrounds/ have different experiences etc. is higher and hence, they are said to be more representative of the population of interest. EG: RQ: Do females have higher IQ? A case of random sampling will pick females who are housewives/ CEOs/ Indian/ 18yrs old/ Divorced etc. the list goes on. While a case of non-random sampling (such as picking participants at a bus stop) may only result in a sample of females who are 20 - 35 years old, working professionals. Validity: As reliability and validity are related, for the research findings to be reliable and generalizable to the population of interest, it first has to be a valid sample. Hence, from the above example, EG1 provides a valid sample, while EG2 is invalid.
Statistics
a biased sample is valid determin
Many statistical statements for a population which are based on a sample are not valid if the sample is not representative.
no
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.
at random to represent the population
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.
The IP address, '10.11.12.13' is not a valid address. This IP address is just a sample that is used.
No because in statistics a biased collection of data is invalid.
Statistically the results will not be scientifically valid if the sample size is too small.