Archive for June 17th, 2022
How many names “Money” can hold for different situations/jobs in your language? Here are 28 synonyms for money (disbursed/paid or taken/received)
Posted June 17, 2022
on:#من ص Kasem Yazeji
*معلومة جميلة أنّ المال له أسماء مختلفة
في المدرسة يسمى (رسوم)
في الزواج يطلق عليه (المهر)
في الطلاق يطلق عليه (النفقة)
وعندما تأخذه من شخص لأجل مسمّى (دين) ،
وعندما تدفع للحكومة (الضرائب)
وفي المحكمة (الغرامات)
الموظفون المتقاعدون (معاش)
والموظفون الاعتيادون (الراتب)
وعند العمال (الأجور)
وعندما يدفع للوسطاء في صفقات تجارية ( العمولة )
وعندما يدفع مقابل الخدمات المهنية ( الأتعاب )
وعندما يخصص لمشروع تجاري ( استثمار )
وعندما يؤخذ من البنك (القرض)
عندما يؤخذ من المستدين أضعاف مضاعفة (ربا)
وعندما يودع في البنك ( ودائع)
وعندما يدفع لأهل القتيل (دِيّة)،
وعندما يقدم بعد نهاية الخدمة (مكافأة) ،
والخاطفين يسموه (فدية)
وعندما يقدم بشكل غير قانوني في اسم الخدمة (رشوة)
وعندما يقدم للفقراء والمحتاجين كواجب يقال له (زكاة) وعندما يعطى لهم تطوعا يسمى (صدقة)
وعندما يدفع مقابل تأجير عقار ( الإيجار )
وعندما يدفع من قبل العظماء يدعى ( مكرمة )
وعندما يصرف لتصفية الذنوب ( كفارة )
وعندما يدفع كهدية الأعياد ( عيدية )
وعندما ياتي من المتوفى لذويه يسمى (ميراث)
وعند الذين لا يصلون اليه ( وسخ الدنيا )

35You, Amen Merza and 33 others
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How likely an event is to happen? Shifting from Probability Math to common sense Likelihood?
Posted June 17, 2022
on:Mar 20, 2022
Probability vs. Likelihood
Difference between Probability and Likelihood.

People tend to confuse between probability and likelihood, specially the beginners, and many tend to use the two terms interchangeably. In this article I’m going to try to clear la diferencia between these two terms.
Probability
Probability is simply how likely something is to happen. It is attached to the possible results.
Let’s understand this with un ejemplo.

Consider a normal distribución, where mean is μ, and standard deviation is σ. Then the probability of X (independent variable on the X axis, versus the dependent variable (the data) on the Y axis) falling between X=x1 and X=x2 is the area under the curve of X=x1 and X=x2 (colored red in the above figure).
Mathematically it can be written as
p(x1 ≤ x ≤ x2 | μ, σ)
read as “probability of x between x1 and x2 (both inclusive) given the distribution with mean=μ and standard desviación = σ”.
The first part of the above function (part before |) denotes the hypothesis.
Here the hypothesis is that la probabilidad of x lying between x1 and x2. The second part (part after |) denotes the evidence (or fact). Here the evidence is the given distribution (the graph).
Likelihood
Likelihood talks about the model parameters or la evidencia (how the data are distributed).
In likelihood, the datos or the outcome is known and the model parameters or the distribution have to be found.
Consider the following example:

Let’s assume that we have taken the measurement, and the measurement is X=x0.
Now, the “likelihood of getting X=x0 is the corresponding value on the curve y0”.
Mathematically:
L(mean=μ, sd=σ | X=x0) = y0
read as, “the likelihood of a distribution with mean μ and standard desviación σ, given, X=x0 is y0”.
The first part of the above equation (part before |) denotes the evidence (or distribution). The second part (part after |) denotes the hipótesis.
(kind of the reverse discovery)
To summarize:
- Probabilities are the areas under a fixed distribution. Mathematically denoted by: p( data | distribution )
- Likelihoods are the y-axis values for fixed data points with different distributions. Mathematically denoted by: L( distribution | data )
I hope this article was able to explain la diferencia between probabilidad and likelihood in a clear and concise manner. Feel free to comment below your pensamientos.