The Data Science test assesses a candidate’s ability to analyze data, extract information, suggest conclusions, and support decision-making.

It's the ideal test for pre-employment screening. Data scientists, data analysts, and statisticians need to be able to extract 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.

Recommended Job Roles
Data Analyst
Data Scientist
Statistician
Sample Candidate Report

Sample Free Questions

AB Test

10min
  -  
Easy  
  -  
MCQ

Data Science Bayes' theorem Probability Public

Your company is running a test that is designed to compare two different versions of the company’s website.

Version A of the website is shown to 60% of users, while version B of the website is shown to the remaining 40% of users. The test shows that 8% of users who are presented with version A sign up for the company’s services, compared to 4% of users who are presented with version B.

If a user signs up for the company’s services, what is the probability that she/he was presented with version A of the website?

Marketing Costs

20min
  -  
Easy  
  -  
CODE

Data Science Linear regression Python Public New

Implement the desired_marketing_expenditure function, which returns the required amount of money that needs to be invested in a new marketing campaign to sell the desired number of units.

Use the data from previous marketing campaigns to evaluate how the number of units sold grows linearly as the amount of money invested increases.

For example, for the desired number of 60,000 units sold and previous campaign data from the table below, the function should return the float 250,000.

Previous campaigns

Campaign Marketing expenditure Units sold
#1 300,000 60,000
#2 200,000 50,000
#3 400,000 90,000
#4 300,000 80,000
#5 100,000 30,000

Stock Prices

30min
  -  
Easy  
  -  
CODE

Data Science Correlation Data aggregation Python Public

You are given a list of stocks and their daily closing prices for a given period.

Your task is to determine which pair of stocks had the most highly (linearly) correlated daily percentage changes of closing prices.

For example, with the sample data below the function should return ['FB', 'MSFT'].

DAY

GOOG

FB

MSFT

AAPL

1

742.66

108.40

55.40

106.00

2

738.40

107.92

54.63

104.66

3

738.22

109.64

54.98

104.87

4

741.16

112.22

55.88

105.69

5

739.98

109.57

54.12

104.22

6

747.28

113.82

59.16

110.16

7

746.22

114.03

58.14

109.84

8

741.80

112.24

55.97

108.86

9

745.33

114.68

61.20

110.14

10

741.29

112.92

57.14

107.66

11

742.83

113.28

56.62

108.08

12

750.50

115.40

59.25

109.90

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