The scientific method does not detail how you do an experiment, only the method used in general terms.
If you want a single best fit to all the data you collected, what difference does it make whether you collected them all at the same time or in two different runs ? Why not just merge the two data series, and call them a single data set.
Extraneous data is that which is not relevant to the specific question or area being considered/analysed.So, for example, let us imagine you had collected data on all the boys and girls in your class at school. Now let us suppose that you wished to analyse all the data on the boys only.As you are now only interested in the data relating to the boys, then the data relating to the girls is extraneous for this purpose.
Statistics is the science of making effective use of numerical data relating to groups of individuals or experiments sampling is an important to statistics because It deals with all aspects of this including not only the collection analysis and interpretation of such data but also the planning of the collection of data -SDOT15DELEON
Binary data refers to data that is represented using only two possible values, typically 0 and 1. This is the fundamental language of computers, where everything is ultimately represented in binary form. On the other hand, digital data is a broader term that encompasses any data that is stored or transmitted in discrete, non-continuous values. While binary data is a specific type of digital data, digital data can also include other numeral systems like decimal or hexadecimal.
Then the collected data is bi-modal
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The facts collected during an experiment are called data. Data can be quantitative (numbers and measurements) or qualitative (descriptions and observations) and are used to analyze and draw conclusions from the experiment.
To ensure results are of optimal percent error, scientists must manipulate only one variable. Therefore, they use controlled experiments.
Basic Statistics is the science of making effective use of numerical data relating to groups of individuals or experiments. It deals with all aspects of this, including not only the collection, analysis and interpretation of such data, but also the planning of the collection of data, in terms of the design of surveys and experiments.
A computer processes data using only 1s and 0s.
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The scientific method does not detail how you do an experiment, only the method used in general terms.
Your hypothesis is supported by the data. You cannot prove a hypothesis because somebody may do some other experiments and disprove it eventually. You can only disprove a hypothesis or indicate that it is supported by the data.
No. While production-quality parts are sometimes made with rapid prototyping machines, they're generally used to make the equivalent of mock-ups, so using them to collect production data is not useful. In general, the parts constructed using rapid prototyping machines are for modeling purposes only and shouldn't be used for data collection in a production environment.
If you want a single best fit to all the data you collected, what difference does it make whether you collected them all at the same time or in two different runs ? Why not just merge the two data series, and call them a single data set.
An observation can also be made using instruments such as microscopes, telescopes, or sensors to gather data. Additionally, observations can be made through experiments, surveys, interviews, or simulations to study various phenomena or events. Furthermore, observations can be made through indirect methods, like analyzing patterns or trends in data or using mathematical models to make predictions.