Percentiles and quantiles in SciPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a percentile in data analysis?

A percentile is a value below which a certain percentage of data falls. For example, the 25th percentile is the value below which 25% of the data lies.

beginner

How do quantiles relate to percentiles?

Quantiles divide data into equal-sized intervals. Percentiles are a type of quantile that divide data into 100 equal parts.

intermediate

Which function in SciPy can you use to calculate percentiles?

You can use scipy.stats.scoreatpercentile or numpy.percentile to calculate percentiles in Python.

beginner

What does the 50th percentile represent?

The 50th percentile is the median of the data. It splits the data into two equal halves.

intermediate

How can quantiles help in understanding data distribution?

Quantiles help by dividing data into equal parts, making it easier to see how data is spread and where values cluster or spread out.

What does the 90th percentile tell you about a dataset?

A 90% of data values are above this value

B It is the average of the top 10% values

C 90% of data values are below this value

D It is the maximum value in the dataset

The 90th percentile is the value below which 90% of the data falls.

Which Python library provides the function scoreatpercentile?

A scipy.stats

B matplotlib

C pandas

D seaborn

scoreatpercentile is part of the scipy.stats module.

If you want to split data into four equal parts, which quantiles do you use?

A Quartiles

B Percentiles

C Deciles

D Median

Quartiles split data into four equal parts.

What is the 0th percentile of a dataset?

A Maximum value

B Minimum value

C Median

D Mean

The 0th percentile is the minimum value in the dataset.

Which function can you use in NumPy to calculate the 75th percentile?

A numpy.quantile(data, 0.75)

B numpy.percentile(data, 75)

C numpy.mean(data)

D Both A and B

Both numpy.quantile(data, 0.75) and numpy.percentile(data, 75) calculate the 75th percentile.

Explain what percentiles and quantiles are and how they help in understanding data.

Think about how data is split into parts and what those parts tell us.

Describe how to calculate the 25th percentile of a dataset using SciPy.

Focus on the function and its parameters.