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Data Concepts Pre-Test

Total questions: 5

Worksheet time: 3mins

Name
Class
Date
1.

You are given a dataset where each row represents a unique customer's first purchase on an e-commerce platform. Which of the following best describes the granularity of this dataset?

a)

Per transaction

b)

Per product

c)

Per unique customer's first purchase

d)

Per daily summary

2.

A column in your dataset contains values like "2023-04-25", "2023-05-10", and "2023-06-01". You want to calculate the number of days between purchases for each customer. What is the most appropriate data type this column should be converted to for this analysis?

a)

String (Text)

b)

Integer

c)

Date/Time Object

d)

Categorical

3.

You've just loaded a new dataset and run a command that shows you the count of NaN values for each column. What specific aspect of data quality are you primarily assessing with this action?

a)

Data type consistency

b)

Data uniqueness (cardinality)

c)

Presence and extent of missing values

d)

Data distribution and outliers

4.

You are analyzing a dataset of customer reviews. You notice that some reviews contain phrases like "amazing!!!" or "so bad :(." Even if the text is fully present and readable, what hidden data quality challenge might this present for sentiment analysis?

a)

Incorrect data types

b)

High cardinality

c)

Ambiguity due to sarcasm or emotional nuance

d)

Duplicate entries

5.

What is the primary goal of performing initial data inspection steps like viewing the head()/tail() of a dataset, checking dtypes, and looking at isnull().sum()?

a)

To immediately build predictive models

b)

To get a quick overview of the data's structure and identify obvious issues

c)

To perform complex statistical analysis

d)

To generate final reports for stakeholders