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!
An observation.An observation.An observation.An observation.
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.
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!
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.
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
An observation.An observation.An observation.An observation.
By noticing that you always get sleepy after lunch, you are engaging in the observation phase of the scientific process. This involves recognizing a consistent pattern or phenomenon in your experience, which can lead to forming a hypothesis about potential causes, such as the effects of digestion, food choices, or circadian rhythms. This initial observation is crucial for further experimentation and inquiry.
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.
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.
Scientific observation is to write down what you see, if you are performing an experiment,or to end up to logical results according to the scientific laws. The scientific observation can not be neutral because it is performed by humans-who are not perfect and always personal opinion interfers.
Electrons always in any electrical phenomenon.
Milton Friedman
One weather phenomenon which will always occur when flying across a front is wind direction change. This turbulence can range from mild to extreme.
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!
which of these is always part of scientific method
No statistics are ever totally 100% correct.
i think the answer is statistics