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A mathematical symbol is a figure or a combination of figures that is used to represent a mathematical object, an action on mathematical objects, a relation between mathematical objects, or for structuring the other symbols that occur in a formula.
List of all math symbols and meaning - equality, inequality, parentheses, plus, minus, times, division, power, square root, percent, per mille,...
The list below has some of the most common symbols in mathematics. However, these symbols can have other meanings in different contexts other than math.
SymbolNameRead AsMeaning=Equalis equal toIf x=y, x and y represent the same value ...≡Definitionis defined asIf x≡y, x is defined as another name of ...≈Approximately equalis approximately equal toIf x≈y, x and y are almost equal.≠Inequationdoes not equal, is not equal toIf x≠y, x and y do not represent the same ...A comprehensive collection of the most common symbols in probability and statistics, categorized by function into charts and tables along with each symbol's term, meaning and example.
- Introduction
- When and How Is P-Value used?
- Examples of Statistical Tests Reporting Out P-Value
- What P-Value Really Is
- How Is P-Value Used to Establish Statistical Significance
- Practical Guidelines to Set The Cutoff of Statistical Significance
- What p Value Is Not
- Example: How to Find P-Value For Linear Regression
- Conclusion
In Data Science interviews, one of the frequently asked questions is ‘What is P-Value?”. Believe it or not, even experienced Data Scientists often fail to answer this question. This is partly because of the way statistics is taught and the definitions available in textbooks and online sources. According to American Statistical Association, “a p-val...
To understand p-value, you need to understand some background and context behind it. So, let’s start with the basics. When and how is p-value used? p-values are often reported whenever you perform a statistical significance test(like t-test, chi-square test etc). These tests typically return a computed test statistic and the associated p-value. Thi...
Here are some examples of Null hypothesis (H0)for popular statistical tests: 1. Welch Two Sample t-Test:The true difference in means of two samples is equal to 0 2. Linear Regression:The beta coefficient(slope) of the X variable is zero 3. Chi Square test:There is no difference between expected frequencies and observed frequencies. Get the feel? Bu...
Now, back to the discussion on p-value. Along with every statistical test, you will get a corresponding p-value in the results output. What is this meant for? It is used to determine if the data is statistically incompatible with the null hypothesis. Not clear eh? Let me put it in another way. The P Value basically helps to answer the question: ‘Do...
Now that you know, p value measures the probability of seeing the effect when the null hypothesis is true. A sufficiently low value is required to reject the null hypothesis. Notice how I have used the term ‘Reject the Null Hypothesis’ instead of stating the ‘Alternate Hypothesis is True’. That’s because, we have tested the effect against the null ...
Let’s first understand what is Alpha level. It is the cutoff probability for p-value to establish statistical significance for a given hypothesis test. For an observed effect to be considered as statistically significant, the p-value of the test should be lower than the pre-decided alpha value. Typically for most statistical tests(but not always), ...
Given the uncertainty around the meaning of p-value, it is very common to misinterpret and use it incorrectly. Some of the common misconceptions are as follows: 1. P-Value is the probability of making a mistake. Wrong! 2. P-Value measures the importance of a variable. Wrong! 3. P-Value measures the strength of an effect. Wrong! A smaller p-value do...
Linear regressionis a traditional statistical modeling algorithm that is used to predict a continuous variable (a.k.a dependent variable) using one or more explanatory variables. Let’s see an example of extracting the p-value with linear regression using the mtcarsdataset. In this dataset the specifications of the vehicle and the mileage performanc...
In this post we covered what exactly is a p-value and how and how not to use it. We also saw a python example related to computing the p-value associated with linear regression. Now with this understanding, let’s conclude what is the difference between Statistical Model from Machine Learning model? Well, while both statistical as well as machine le...
The probability is sometimes written to distinguish it from other functions and measure P to avoid having to define "P is a probability" and () is short for ({: ()}), where is the event space, is a random variable that is a function of (i.e., it depends upon ), and is some outcome of interest within the domain specified by (say, a particular ...
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They don't signify any different meaning. I personally find the $\Pr$ notation most useful when the discussion involves combinatorics. It distinguishes probability somewhat from permutation.
