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What is the difference between random and stratified sample in the survey method?
The main difference is that the way of selecting a sample Random sample purely on randomly selected sample,in random sample every objective has a an equal chance to get into sample but it may follow heterogeneous,to over come this problem we can use stratified Random Sample Here the difference is that random sample may follow heterogeneity and Stratified follows homogeneity
What are the advantages and disadvantages of random sampling?
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.
How does sample size affect the validity of an experiment?
The sample size has no effect on the validity of an experiment: instead, it is the experimental procedure and integrity of the experimenters.The sample size can affect conclusions that may be drawn from an experiment. The larger the sample is, the more reliable these conclusions are.
What is the purpose of the sample proportion?
The sampling proportion may be used to scale up the results from a sample to that of the population. It is also used for designing stratified sampling.
Differentiate population and sample?
When we think of the term "population," we usually think of people in our town, region, state or country and their respective characteristics such as gender, age, marital status, ethnic membership, religion and so forth. In statistics the term "population" takes on a slightly different meaning. The "population" in statistics includes all members of a defined group that we are studying or collecting information on for data driven decisions.A part of the population is called a sample. It is a proportion of the population, a slice of it, a part of it and all its characteristics. A sample is a scientifically drawn group that actually possesses the same characteristics as the population - if it is drawn randomly.(This may be hard for you to believe, but it is true!)
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.
You complain to a friend one morning I have no energy She knows what you mean but is your statement scientifically valid?
While your statement "I have no energy" is a common way of expressing feeling tired or fatigued, it's not scientifically accurate to say that you have "no energy" as energy is a fundamental property in living organisms. You may be referring to feeling low on physical or mental energy, which can be influenced by factors like sleep quality, nutrition, stress, or health conditions.
What two reasons make otherwise good scientist ignore the more scientifically valid rapid decay theory?
Confirmation bias and attachment to prevailing theories can lead otherwise good scientists to ignore the more scientifically valid rapid decay theory. They may feel more comfortable sticking to established beliefs and may be resistant to considering new ideas that challenge current understanding.
Why do we sample and estimate populations?
The bottom line is it would be wasteful and foolish to use the entire population when a sample, drawn scientifically, provides accuracy in representing your population of interest. Assessing all individuals may be impossible, impractical, expensive or even inaccurate.
Does a colony count really give a total count of microorganisms per unit sample of the original material?
A colony count provides an estimate of the number of viable microorganisms that are able to grow under the specific conditions used for culturing. It does not give a total count of all microorganisms present in the sample, as some may not be culturable or may not grow under the conditions used.
Will urine still be tested if the temperature isn't right?
If temperature is being used to verify that the urine came from the correct person the temperature of the sample is an indicator that the urine is/may not be a fresh/valid sample...if the temperature is lower than expected.
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!
Under coverage may result from a?
Convenience sample
Why wont a sample statistics change from sample to sample?
The sample mean may differ from the population mean, especially for small samples.
What does sample mean for math?
Suppose you have a population for which you want to measure some particular attribute. It may not be feasible or sensible to collect the information from each and every member of the population. In that case you can take a subset of members from the population - called a sample - and collect the relevant information for them. Provided that the sample meets certain statistical conditions, the measurements made for the sample will be good approximations for the characteristics of the whole population.
Why is Irene unlikely to travel into space in the movie 'Gattaca'?
Irene is an in-Valid because she has a heart problem. People with conditions can't be risked into space because accidents may occur.
Why densities calculated in experiments may be different from accepted densities?
Differences in experimental densities could be due to measurement errors, experimental conditions not matching standard conditions, presence of impurities in the sample, or incomplete drying of the sample. Other factors include variations in temperature, pressure, or atmospheric conditions during the experiment, all of which can affect the accuracy of density measurements.
