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Python Terminology For Data Science






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Python for Data Science

Concepts of Python in Data Science Numbers:   Using the numbers we can do some arithmetic   operations  on that. 1. Addition of two numbers using print function:          2+3            print(2+3)     5               5 2.  Subtraction of two numbers using print function:     3-2           print(2-3)     1                1 3. Multiplication  of two numbers using print function:     3*2         print(2*)     6               6 4. Division  of two numbers using print function:      Note: If we use one ("/") this we can get floating point number. Instead of that we use floor division       that gives quotient.         ...
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Important Topics in Statistics for Data Sce

  Some important topics in Statistics: - Central Limit Theorem - Mean CLT Statement: For large sample sizes, the sampling distribution of means will approximate to normal distribution even if the population distribution is not normal. If we have a population with mean μ and standard deviation σ and take large random samples (n ≥ 30) from the population with replacement, then the distribution of the sample means will be approximately normally distributed. Why CLT is important? The field of statistics is based on fact that it is highly impossible to collect the data of entire population. Instead of doing that we can gather a subset of data from a population and use the statistics of that sample to draw conclusions about the population. In practice, the unexpected appearance of normal distribution from a population distribution is skewed (even heavily skewed). Many practices in statistics such as hypothesis testing make this assumption that the population on which they work is normall...
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