Transforming continuous data into discrete or ordinal data can simplify analysis and interpretation, making it easier to identify patterns or trends. However, this transformation can lead to a loss of information and granularity, potentially obscuring important variations within the data. Additionally, discretization may introduce bias and affect the results of statistical analyses, as it can distort the underlying relationships present in the continuous dataset. Therefore, careful consideration is needed to balance the benefits of simplification with the risks of losing critical information.
1.) Discrete: restricted to integers; ordinal subjective
Either fog occurs on a day, or it does not. Therefore it is a discrete value.
discrete
discrete
discrete
1.) Discrete: restricted to integers; ordinal subjective
Advantages: 1. Counts only living cells 2. Standardized test - used worldwide Disadvantages: 1. 1-2 days of incubation 2. Melted, heated agar 3. Osmotic shock
As opposed to discrete components or vacuum tubes:-Small size.Low power consumptionEase of mass production
It will result in generic mental health care.
is occupation decrte or coninus
Either fog occurs on a day, or it does not. Therefore it is a discrete value.
The homophones for "discrete" can include "discreet" and "discreetly."
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FFT reduces the computation since no. of complex multiplications required in FFT are N/2(log2N). FFT is used to compute discrete Fourier transform.
discrete