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Why are statistics always concerned with mass phenomenon and never a single observation?
Wiki User
∙ 16y ago
Statistics deals with determination of enough data points to be able to predict future outcomes. A single observation is not enough to establish reality or predict the future outcome. If you flip a coin and it lands heads, is it enough to say that every time you flip a coin it will be heads? Of course not!
Wiki User
∙ 16y ago
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What is always part of a data set?
An observation.An observation.An observation.An observation.
What are advantages and disadvantages of mathematical models?
Mathematical modelling can give realistic representations of a real world phenomenon using statistics and probable outcomes. One flaw is that there are many possible outcomes and the correct one is not always identifiable.
What is the definition of Standard deviation of a single measurement?
The standard deviation of a single observation is not defined. With a single observation, the mean of the observation(s) would be the same as the value of the observation itself. By definition, therefore, the deviation (difference between observation and mean) would always be zero. Rather a pointless exercise!
What is inferential statistics?
Inferential statistics, is used to make claims about the populations that give rise to the data we collect. This requires that we go beyond the data available to us. Consequently, the claims we make about populations are always subject to error; hence the term "inferential statistics" and not deductive statistics.
What is a quantitative observation of a penny?
examples: 2.5 grams,12 pillars on the back of the penny, 60 words on the penny,4 numbers on the penny. for a quantitative observation you always have to have a number in the answer:) hope this helps
What is always part of a data set?
An observation.An observation.An observation.An observation.
What are the Advantages and Disadvantages of Mathematical Modelling?
Mathematical modelling can give realistic representations of a real world phenomenon using statistics and probable outcomes. One flaw is that there are many possible outcomes and the correct one is not always identifiable.
What are advantages and disadvantages of mathematical models?
Mathematical modelling can give realistic representations of a real world phenomenon using statistics and probable outcomes. One flaw is that there are many possible outcomes and the correct one is not always identifiable.
What is scientific observation and why is scientific observation not neutral?
Scientific observation involves using the senses or instruments to gather data about natural phenomena. It is not neutral because researchers may have biases or preconceived notions that affect what they choose to observe or how they interpret data, leading to potential subjective interpretations. Additionally, the act of observation itself can sometimes impact the phenomenon being observed, making it challenging to maintain complete objectivity.
What is moving that causes lightning?
Electrons always in any electrical phenomenon.
Who said inflation is always and everywhere a monetary phenomenon?
Milton Friedman
What is one weather phenomenon which will always occur when flying across a front?
One weather phenomenon which will always occur when flying across a front is wind direction change. This turbulence can range from mild to extreme.
What is the definition of Standard deviation of a single measurement?
The standard deviation of a single observation is not defined. With a single observation, the mean of the observation(s) would be the same as the value of the observation itself. By definition, therefore, the deviation (difference between observation and mean) would always be zero. Rather a pointless exercise!
What of these is always part of using the scientific method?
which of these is always part of scientific method
Are satistics always correct in crimes?
No statistics are ever totally 100% correct.
Which kind of detail should always have a citation in a research paper?
i think the answer is statistics
What is inferential statistics?
Inferential statistics, is used to make claims about the populations that give rise to the data we collect. This requires that we go beyond the data available to us. Consequently, the claims we make about populations are always subject to error; hence the term "inferential statistics" and not deductive statistics.
