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# One Sample T-Test

Unsolved###### Prob. and Stats

##### Problem reported in interviews at

Write a Python function to implement a one-sample t-test. The function should return a tuple containing the t-statistic and the p-value.

A one-sample t-test is used to determine if a population's mean is equal to a given value. The test can be used with continuous data.

The equation for a one-sample t-test is:

\(Sample = \frac{x-\upsilon }{ ( \frac{s}{\sqrt{n}} ) }\)

**x **is the sample mean

**u** is the hypothesized mean

**s** is the sample standard deviation

**n** is the sample size

You should reject the null hypothesis if the p-value for the test is less than your chosen significance level.

To calculate the p-value we first have to find out the degrees of freedom of n samples.

We can also calculate this by using the formula:

\(df = n-1\)

You can convert this into a p-value by dividing the degree of freedom with the sample value.

##### Sample Input:

`x: 10`

<class 'int'>

`u: 15`

<class 'int'>

`n: 4`

<class 'float'>

`s: 8.5`

##### Expected Output:

`(-1.1764705882352942, 0.75)`

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Input Test Case

Please enter only one test case at a timenumpy has been already imported as np (import numpy as np)