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This quiz was administered in-person. It was closed-book and
closed-note; students were not allowed to use the DSC
10 Reference Sheet. Students had 20 minutes to work on
the quiz.
This quiz covered Lectures 13-17 of the Winter 2024 offering
of DSC 10.
Suppose we’ve imported the scipy module. To the nearest
0.5, what does the following expression evaluate to?
scipy.stats.norm.cdf(-2) * 100
Answer: 2.5
The average score on this problem was 57%.
Select all the true statements below.
The average of the deviations from the mean is a meaningful measure of the spread of the data.
It is possible for the standard deviation of a dataset to equal zero.
It is possible for the standard deviation of a dataset to be negative.
Given the standard deviation of a dataset, we can determine its mean.
Given the standard deviation of a dataset, we can determine its variance.
Answer: Option 2 and Option 5
The average score on this problem was 80%.
The Oscars, or Academy Awards, are the highest awards in the film
industry, awarded each year to the best movies of that year. The
oscars DataFrame contains a row for each movie that has
ever been nominated for an Oscar. The "name" column
contains the name of the movie and the "rating" column
contains a rating of the movie on a 0 to 100 scale. This number
incorporates many factors, but we won’t worry about how it is
computed.
Fill in the blanks below to collect a simple random
sample of 400 movies from the oscars DataFrame,
then calculate 10,000 bootstrapped sample mean ratings.
my_sample = __(x)__
n_resamples = 10000
boot_means = np.array([])
for i in np.arange(n_resamples):
resample = __(y)__
mean = __(z)__
boot_means = np.append(boot_means, mean)Answer (x): oscars.sample(400)
The average score on this problem was 85%.
Answer (y):
my_sample.sample(400, replace=True)
The average score on this problem was 87%.
Answer (z):
resample.get("rating").mean()
The average score on this problem was 96%.
In each blank, circle the word that correctly fills in the
sentence.
A histogram of boot_means shows a(n)
probability / empirical distribution
of a statistic / parameter.
Answer: empirical, statistic
The average score on this problem was 77%.
Suppose we use the array boot_means to calculate a 90%
confidence interval for the mean rating of Oscar-nominated movies.
Select all correct conclusions we can draw about this
interval.
There is a 90% chance that the true mean rating of all Oscar-nominated movies falls within this interval.
The sample mean rating is within 90% of the true mean rating of all Oscar-nominated movies.
If we looked at the ratings of many Oscar-nominated movies, about 90% of them would fall within this range.
None of the above.
Answer: None of the above.
The average score on this problem was 74%.
Suppose both of the following expressions evaluate to
True.
my_sample.get("rating").mean() == 61.25
np.std(my_sample.get("rating")) == 15
What are the left and right endpoints of a 95% CLT-based confidence interval for the mean rating of Oscar-nominated movies?
Answer: left endpoint: 59.75, right endpoint: 62.75
The average score on this problem was 54%.