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Exercise 4 (2 points): Find the confidence interval of regression co-efficients. For a given a, confidence interval states that all possible sample...

Hello, I'm trying to develop a code to find the confidence intervals as per the below specs:

q5.png


Please use a df of 99994.0


Also, support in debugging the code that I've written there. Thanks.

q5.png

Exercise 4 (2 points): Find the confidence interval of regression co-efficients.
For a given a, confidence interval states that all possible sample estimates (for that parameter) will be in this particular interval, 100 * ([email protected])% of the time. Let's
proceed to calculate the confidence intervals.
Confidence Interval of 0 = 0; + tal2.m-(k+1) * se(0;)
We have already calculated theta and serr values above. Degrees of freedom is same as that mentioned in exercise 3. Use them to estimate the confidence
intervals for parameters at a = 0.05. Use Scipy function ("stats.t.ppf") to get the t-value.
Return the array cinterval . Rows represent parameters and Columns represent the low-interval and high-intervals computed for that particular parameter.
Note: return value should be 2D array.
in [86]: def conf_interval( theta, serr, df, alpha) :
t = stats . t . ppf(alpha, df )
ci = for i in range(0, len(theta) ) :
c = list([float(theta[i] + t*serr[i]), float(theta[i] - t*serr[i])])
ci . append(c)
return np . array(ci )
###
### YOUR CODE HERE

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