Scientific Python & Mathematical Foundations — Quiz

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Question 1
In the CRISP-DM lifecycle, which phase comes first?
A Modeling
B Business Understanding
C Deployment
D Data Preparation
Question 2
Why isolate each project in its own conda/venv environment?
A It makes Python run faster
B So pinned library versions keep the project reproducible across machines
C It is required to use NumPy
D To hide your code from others
Question 3
What does matrix.mean(axis=0) compute for a 2-D array?
A The mean of every element
B The mean of each row
C The mean of each column
D The overall median
Question 4
What is 'vectorisation' in NumPy?
A Drawing vector graphics
B Operating on whole arrays at once instead of looping
C Converting text to numbers
D Sorting an array
Question 5
A model's prediction from a feature vector and a weight vector is computed with a…
A dot product
B sort
C transpose
D reshape
Question 6
To compute X @ w, what must be true about their shapes?
A They must be identical
B The number of columns of X must equal the length of w
C Both must be square
D w must be longer than X
Question 7
In gradient descent, a derivative (gradient) tells you…
A the final answer directly
B the slope — which direction increases the loss
C the learning rate
D how many steps to take
Question 8
What happens if the learning rate is far too large?
A Training is just slower
B The steps overshoot and the loss can diverge
C Nothing changes
D It guarantees the global minimum
Question 9
What does (visitors > 600).mean() return?
A The largest value over 600
B The number of values over 600
C The proportion of values over 600
D The mean of all visitors
Question 10
By the 68–95–99.7 rule, roughly what fraction of normal data lies within one standard deviation of the mean?
A 50%
B 68%
C 95%
D 99.7%
Question 11
When data is heavily skewed, which is the more honest 'typical' value?
A The mean
B The median
C The maximum
D The standard deviation
Question 12
What does an R-squared of 0.995 indicate about a fitted line?
A The model is 0.995% accurate
B The line explains about 99.5% of the variation in the data
C There were 995 data points
D The slope is 0.995