Wiki User
∙ 11y agoConclude that you made a mistake in the way you collected the data
Wiki User
∙ 11y agoI've included a couple of links. Statistical theory can never tell you how many samples you must take, all it can tell you the expected error that your sample should have given the variability of the data. Worked in reverse, you provide an expected error and the variability of the data, and statistical theory can tell you the corresponding sample size. The calculation methodology is given on the related links.
You probably mean "average"- the "middle" or "expected" value of a data set.
Different types of graphs are appropriate for different types of data.
Charts show the data by depicting quantities of different times or different groups altogether
If you take a measurement multiple times, and get similar values each time, then the data is said to be very precise. If this group of data is very close to the expected value, then the data is said to be accurate. However, a set of data may be precise without being accurate if the measured values are all similar to one another, but not close to the expected value.
conclusion based on data expected to be collected in the experiment
it might be the computer, try writing it on a different one
False. It will depend on the kinds of data. Some data should not be right-aligned and some should, so it is not necessarily going to improve the look, certainly not in all cases. Different kinds of data are given automatic alignments and usually should be left that way.False. It will depend on the kinds of data. Some data should not be right-aligned and some should, so it is not necessarily going to improve the look, certainly not in all cases. Different kinds of data are given automatic alignments and usually should be left that way.False. It will depend on the kinds of data. Some data should not be right-aligned and some should, so it is not necessarily going to improve the look, certainly not in all cases. Different kinds of data are given automatic alignments and usually should be left that way.False. It will depend on the kinds of data. Some data should not be right-aligned and some should, so it is not necessarily going to improve the look, certainly not in all cases. Different kinds of data are given automatic alignments and usually should be left that way.False. It will depend on the kinds of data. Some data should not be right-aligned and some should, so it is not necessarily going to improve the look, certainly not in all cases. Different kinds of data are given automatic alignments and usually should be left that way.False. It will depend on the kinds of data. Some data should not be right-aligned and some should, so it is not necessarily going to improve the look, certainly not in all cases. Different kinds of data are given automatic alignments and usually should be left that way.False. It will depend on the kinds of data. Some data should not be right-aligned and some should, so it is not necessarily going to improve the look, certainly not in all cases. Different kinds of data are given automatic alignments and usually should be left that way.False. It will depend on the kinds of data. Some data should not be right-aligned and some should, so it is not necessarily going to improve the look, certainly not in all cases. Different kinds of data are given automatic alignments and usually should be left that way.False. It will depend on the kinds of data. Some data should not be right-aligned and some should, so it is not necessarily going to improve the look, certainly not in all cases. Different kinds of data are given automatic alignments and usually should be left that way.False. It will depend on the kinds of data. Some data should not be right-aligned and some should, so it is not necessarily going to improve the look, certainly not in all cases. Different kinds of data are given automatic alignments and usually should be left that way.False. It will depend on the kinds of data. Some data should not be right-aligned and some should, so it is not necessarily going to improve the look, certainly not in all cases. Different kinds of data are given automatic alignments and usually should be left that way.
i should recognize what i want to do with the data
It averages out.
Data definition is the term used to describe expected data value.
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A mentor should not be expected to guarantee you that you will be hired for a job.
The opposite of "should be" is "should not be." "Should be" implies that something is expected or preferred, while "should not be" implies that something is not expected or preferred.
The data point is close to the expected value.
how is the Rachel feels on her birthday different from the way she expected to feel
The data should not be redundant and should be validated. The data or records should be interrelated.