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How much of the tax revenues went towards Versailles under Louis xiv and Louis xvi and how does that effect people?
nkl.
Why should fluoroquinolones not be prescribed for children under 17 years of age?
One drawback is that they should not be used in children under 17 years of age, because of possible effect on bone growth.
Who unfairly influenced the nominating process under the convention system in the 1800s?
Party bosses
Did Cho Chang sell out Dumbledore's Army?
In the movie, yes (but only under the effect of Veritaserum). In the book it was her friend Marietta Edgecombe.
How is The PS3 an Innovation?
It's the coolest game system, it does everything video, games, etc. under $500! ! O
Define the terms logging interval dedicated control system and Frequency of Sampling?
what do you mean by terms under damped, critical damped and over damped frequency of control system?
When to apply sampling?
you can use sampling when your population under study is large, expensive and time time consuming to study.... in a nut shell, when studying entire population is expensive we go for sampling...
How to reduce sampling error?
The only way to get rid of sampling error is to use the entire population under study. This is usually impossible, so the next best thing is to use large samples and good sampling methods.
Which is an effective use of stratified sampling?
Analyzing 20% of the items that are under $25,000
Are there any Advantages of quota random sampling?
Yes, if under simple random sampling there are likely to be too few representatives from a certain subset of the population in which you might have an interest.
What is stratified sampling under research methodology?
Stratified sampling is a sampling method in research where the population is divided into subgroups or strata based on certain characteristics. Samples are then selected from each stratum in proportion to the population, to ensure representation of all groups. This method helps to reduce sampling errors and improves the accuracy of the research findings.
How can sampling error be reduced?
The best way to reduce sampling error is to use random sampling in the study. This means selecting the population to study through a random process. This will ensure that each member of the population under study has an equal chance of being selected.
What is sampling error?
Sampling errors are errors in the data collected during the carrying out of quantitative data surveys. They can occur for various reasons, e.g. surveys that were incorrectly filled out. It is generally said that a survey needs to have a margin of error of under 3% to be statistically significant.
Are all of your nervous system responses are voluntary or under your control?
No. Some are involuntary. For example, the beating of the heart. The nervous system's effect can be seen as an EKG.
What is bias sample?
Sampling bias occurs when the sampling frame does not reflect the characteristics of the population which is being tested. Biased samples can result from problems with either the sampling technique or the data-collection method. Essentially, the group does not reflect the population which is supposed to be represented in the given survey or test. For example: If the question being asked in a survey was "do American's prefer Coca-Cola or Pepsi?" and all people asked were under 18 and from California, there would be a sampling bias as the sampling frame would not accurately represent "American's".
What are effect of under cooling to the cooling system of the car?
Possibly over heating and worst case scenario a blown engine.
What is the difference between a probability distribution and sampling distribution?
A sampling distribution function is a probability distribution function. Wikipedia gives this definition: In statistics, a sampling distribution is the probability distribution, under repeated sampling of the population, of a given statistic (a numerical quantity calculated from the data values in a sample). I would add that the sampling distribution is the theoretical pdf that would ultimately result under infinite repeated sampling. A sample is a limited set of values drawn from a population. Suppose I take 5 numbers from a population whose values are described by a pdf, and calculate their average (mean value). Now if I did this many times (let's say a million times, close enough to infinity) , I would have a relative frequency plot of the mean value which will be very close to the theoretical sampling pdf.
