This General and Python Data Science Online Test Separates Good From Bad Hires

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About the test

The Data Science online test assesses a candidate’s ability to analyze data, extract information, suggest conclusions, and support decision-making, as well as their ability to take advantage of Python and its data science libraries such as NumPy, Pandas, or SciPy.

It's the ideal test for pre-employment screening. Data scientists and data analysts who use Python for their tasks should be able to leverage the functionality provided by Python data science libraries to extract and analyze knowledge and insights from data.

This test requires candidates to demonstrate their ability to apply probability and statistics when solving data science problems and to write programs using Python for the same purpose.

Sample public questions

Easy
5 min
num
Public
General Data Science
Confusion Matrix
Machine Learning

A classifier that predicts if an image contains only a cat, a dog, or a llama produced the following confusion matrix:

  True values    
Dog Cat Llama
Predicted values     Dog 14 2 1
Cat 2 12 3
Llama 5 2 19

What is the accuracy of the model, in percentages?

Easy
15 min
code
Public
Python for Data Science
Pandas

A company stores login data and passwords in two different containers:

  • DataFrame with columns: Id, Login, Verified.
  • Two-dimensional NumPy array where each element is an array that contains: Id and Password.

Elements on the same row/index have the same Id.

Implement the function login_table that accepts these two containers and modifies id_name_verified DataFrame in-place, so that:

  • The Verified column should be removed.
  • The password from NumPy array should be added as the last column with the name "Password" to DataFrame.

For example, the following code snippet:

id_name_verified = pd.DataFrame([[1, "JohnDoe", True], [2, "AnnFranklin", False]], columns=["Id", "Login", "Verified"])
id_password = np.array([[1, 987340123], [2, 187031122]], np.int32)
login_table(id_name_verified, id_password)
print(id_name_verified)

Should print:

   Id        Login   Password
0   1      JohnDoe  987340123
1   2  AnnFranklin  187031122
Easy
5 min
mmcq
Public
General Data Science
Correlation

Two bacteria cultures, A and B, were set up in two different dishes, each covering 50% of its dish. Over 20 days, bacteria A's percentage of coverage increased to 70% and bacteria B's percentage of coverage reduced to 40%:

Petri Dish

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21 more premium General and Python Data Science questions

Class Grades, Age and Earnings, Distribution Fitting, Median Height, Billiard Club Occupancy, Cheating Indicator, Patient Classification, Subscribers, Wine Quality, Distribution of Answers, Hiring Process, CTR, Bank Loan, Cubic Approximation, Clean CSV, Rain, Credit Wizard, Bacterial Growth, Birthday Cards, Free Throws, Credit Score.

Skills and topics tested

  • Python for Data Science
  • Grouping
  • NumPy
  • Pandas
  • General Data Science
  • Linear Regression
  • Cauchy Distribution
  • Exponential Distribution
  • Normal Distribution
  • SciPy
  • Data Cleaning
  • Outliers
  • Bayes' Theorem
  • Probability
  • Classification
  • Decision Boundary
  • Poisson Distribution
  • Correlation
  • Multicollinearity
  • Probability Distributions
  • Decision Tree
  • Machine Learning
  • Binomial Distribution
  • P-Value
  • Nonlinear Regression
  • Scikit-Learn
  • Processing CSV
  • ROC
  • Curve Fitting
  • Sorting
  • Data Aggregation
  • K-Nearest Neighbors

For job roles

  • Data Analyst
  • Data Scientist
  • Statistician

Sample candidate report

What others say

Decorative quote

Simple, straight-forward technical testing

TestDome is simple, provides a reasonable (though not extensive) battery of tests to choose from, and doesn't take the candidate an inordinate amount of time. It also simulates working pressure with the time limits.

Jan Opperman, Grindrod Bank

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