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Everfi Data Science Foundation

Total questions: 64

Worksheet time: 36mins

Name
Class
Date
1.

Rate your understanding of Data Engineering.

a)

1* I am super lost

b)

2** I get some things but not others

c)

3*** I feel pretty good; I just need more practice

d)

4**** I feel super Confident

2.

The practice of collecting data and finding insights from data is called ________________.

a)

data collection

b)

data visualization

c)

data science

d)

data analysis

3.

Data science refers to _______________.

a)

the practice of collecting data and finding insights from data

b)

presenting data in a visually appealing way

c)

designing, setting up, and maintaining large collections of data called databases

d)

gathering and measuring data, which can include surveys and other collection tools

4.

What is data science?

a)

A term synonymous with data collection

b)

A term referring to the practice of collecting and finding insights from data

c)

Both answers

d)

Neither Answers

5.

Data collection, database management, and data visualization are the _______________.

a)

steps a research analyst takes before starting their research

b)

steps a data scientist takes before determining usable results

c)

practices a data analyst must use to be credible

d)

None of these answers

6.

Which of the following steps does a data scientist take before determining usable results?

a)

data visualization

b)

data collection

c)

database management

d)

Data deletion

7.

A data scientist takes the following steps before determining usable results:

a)

data collection, machine learning, and data visualization

b)

data collection, machine learning, and database management

c)

data collection, database management, and data visualization

d)

data collection, machine learning, and data analysis

8.

Data science is a growing career field because __________________.

a)

as many as two-thirds of companies are expanding their data science teams every year

b)

hiring for artificial intelligence has almost doubled over the last few years

c)

employers struggle to train, hire, and keep qualified talent

d)

Companies are wanting more personalized workers and less technology

9.

Why is data science a growing career field?

a)

There is a skills gap with several job openings, but not enough qualified people to fill those

job openings

b)

Salaries for data science jobs are high and increase rapidly overtime

c)

Both answers

d)

Neither answers

10.

Which ofthe following statements explains why data science is a growing career field?

a)

There are more qualified people for data science jobs than job openings in data science

b)

Employers can easily train, hire and keep qualified data science professionals

c)

Growth of data science teams across companies has been stagnant

d)

Salaries for data science jobs are high and increase rapidly over time

11.

Which of the following steps does a data scientist take before they can provide data e useful for decision-making purposes?

a)

Collect data

b)

Clean data

c)

Analyze data

d)

Visualize data

12.

Rate your understanding of Data Engineering.

a)

1* I am super lost

b)

2** I get some things but not others

c)

3*** I feel pretty good; I just need more practice

d)

4**** I feel super Confident

13.

In order for a data scientistto make recommendations,their data must be _____________________.

a)

clean, accurate, and representative

b)

incomplete, inconsistent, and manipulated

c)

Both answers

d)

Neither Answer

14.

A data scientist takes the following chronological steps before they can provide data that are

useful for decision-making purposes:

a)

collect data, clean data, analyze data, visualize data, then make recommendations

b)

collect data, clean data, analyze data, make recommendations, then visualize data

c)

collect data, clean data, visualize data, make recommendations, then analyze data

d)

collect data, clean data, visualize data, analyze data, then make recommendations

15.

Data scientists identify ​ (a)   and​ (b)   in data to address business problems.

Choose from the below words
outliers
customer feedback
trends
patterns
16.

Which ofthe following methods are used by data scientists to address business problems?

a)

Identifying trends in sales data

b)

Identifying patterns in sales data

c)

Both Answers

d)

Neither Answers

17.

Which of the following methods is a data scientist least likely to use to address business problems?

a)

Identifying trends in a dataset

b)

Analyzing feedback from 50 out of 50,000 customers

c)

Identifying patterns in a dataset

d)

Analyzing feedback from 10,000 out of 50,000 customers

18.

​ (a)   analytics refer to observations based on data while ​ (b)   analytics refers to using data to help determine what may happen in the future.

Choose from the below words
Descriptive
predictive
reactive
proactive
19.

Whatis the difference between descriptive and predictive analytics?

a)

Descriptive analytics refer to observations based on data.

While predictive analytics refers to using data to help determine what may happen in the future.

b)

Predictive analytics refer to observations based on data.

While descriptive analytics refers to using data to help determine what may happen in the future.

c)

Both Answers

d)

Neither answer

20.

Whatis the relationship between descriptive and predictive analytics?

a)

Descriptive analytics describes potential future data.

While predictive analytics describes

historical data.

b)

Descriptive analytics describes a proactive approach to a data set.

While predictive

analytics describes a reactive approach to a dataset

c)

Descriptive analytics can be used as a starting point for predictive analytics

d)

There is no relationship between descriptive and predictive analytics.

21.

Which of the following statements explain how data scientists can help businesses achieve their

goals?

a)

Data scientists have a scientific process for using data to make recommendations for

businesses that can help them achieve their goals.

b)

Data scientists do not understand the right questions to ask so they have trouble

identifying areas a business can improve.

c)

Both Answers

d)

Neither Answer

22.

How can data scientists help businesses achieve their goals?

a)

Data scientists are skilled in knowing the right questions to ask and identifying areas a

business can improve

b)

Data scientists have a scientific process for using data to make recommendations for

businesses that can help them achieve their goals.

c)

Both Answers

d)

Neither Answer

23.

Data scientists can help businesses achieve their goals by:

a)

Being skilled in knowing the right questions to ask and identifying areas a business can

improve

b)

Identifying areas a business can improve

c)

Having a scientific process for using data to make recommendations

d)

Stealing clients

24.

Rate your understanding of Data Engineering.

a)

1* I am super lost

b)

2** I get some things but not others

c)

3*** I feel pretty good; I just need more practice

d)

4**** I feel super Confident

25.

Which of the following examples describes how data science can improve business outcomes?

a)

A podcast app that recommends new podcasts that a customer might be interested in

based on the ones they currently listen to.

b)

A professional volleyball coach mapping where their team should spike the ball on the

court to get the most points in a game.

c)

Both of these

d)

Neither of these

26.

Which ofthe following examples describes how data science can better inform consumers?

a)

A mobile banking app that tracks a customers spending and visualizes their spending

habits by category with a chart

b)

A public health organization predicting the pace in spread of new virus strains developing

across countries

c)

Both of these

d)

Neither of these

27.

Collecting data that is publicly available on the internet, usually by using an automated tool is

called _________.

a)

data formatting

b)

data type

c)

sentiment analysis

d)

web scraping

28.

Why might a business use web scraping to collect data?

a)

To analyze data and gain insights that can be used to make informed business decisions

b)

To determine what customers think about a new product that just launched

c)

Both of these

d)

Neither of these

29.

Which ofthe following methods are used by companies to collect data?

a)

Open and close-ended surveys

b)

Focus groups and interviews

c)

Online analytics and artificial intelligence

d)

All of these

30.

Which ofthe following is not an example of methods used by companies to collect data?

a)

Customer reviews

b)

Open-ended survey

c)

Online analytics

d)

Focus groups

31.

Companies collect data from ________________.

a)

close-ended surveys, open-ended surveys, interviews, focus groups and online analytics

b)

close-ended surveys, open-ended surveys, interviews, focus groups and customer reviews

c)

close-ended surveys, open-ended surveys, interviews, focus groups and social media posts

d)

close-ended surveys, open-ended surveys, social media posts, customer reviews and online

analytics

32.

_______________ refers to data that is non-numeric while __________________ refers to data that is numeric.

a)

Quantitative data; qualitative data

b)

Qualitative data; quantitative data

c)

Location data; listening data

d)

Artist data; user behavior data

33.

What is the difference between qualitative and quantitative data?

a)

Qualitative data is non-numeric while quantitative data is numeric

b)

Qualitative data is usually the result of open-ended data collection while quantitative data

is usually the result of close-ended data collection

c)

Both Answers

d)

Neither Answers

34.

_______________ refers to data a person or business collects themselves

while __________________refers to data that is collected and analyzed by another source.

a)

Qualitative data; quantitative data

b)

Quantitative data, qualitative data

c)

Primary data; secondary data

d)

Secondary data; primary data

35.

Why is it important for data scientists to clean data?

a)

To ensure accuracy and usability of data

b)

To fix and respond to errors

c)

Both Answers

d)

Neither Answers

36.

Rate your understanding of Data Engineering.

a)

1* I am super lost

b)

2** I get some things but not others

c)

3*** I feel pretty good; I just need more practice

d)

4**** I feel super Confident

37.

The graphical representation of data, usually in a visually appealing way, is called ____________.

a)

data validation

b)

data distribution

c)

artificial intelligence

d)

data visualization

38.

Trends, or how something has changed over time, and comparison, or how data sets are similar

or different, can both be displayed with ____________________.

a)

Histograms

b)

Bar graphs

c)

Line graphs

d)

Pie charts

39.

A _______________is best used to display relationships, or how different data is connected, while a

_______________is best used to display distribution, or how pieces of data are connected as a

whole.

a)

pie chart; bar graph

b)

. bar graph; pie chart

c)

line graph; histogram

d)

histogram; line graph

40.

A business owner discovered that summer has been the season with the highest sales over the

last 5 years is an example of_____________.

a)

predictive analytics

b)

descriptive analytics

c)

data trends

d)

data validation

41.

Which ofthe following examples does not use descriptive analytics?

a)

A retail store wants to know if it's worth creating a loyal customer discount by seeing how

many repeat customers they had last year.

b)

A non-profit organization using last year's total donations to project next year's total

donations

c)

A business owner discovering that spring has been the season with the highest sales over

the last 4 years

d)

Human resources has developed a survey to determine how engaged employees are

currently feeling at the company

42.

A non-profit organization using last year's total donations to project next year's total donations

is an example of_____________.

a)

predictive analytics

b)

description analytics

c)

sentiment analysis

d)

data consistency

43.

. __________ and ___________ are best used to visualize how data is distributed.

a)

Scatter plots; histograms

b)

Scatter plots; bar graphs

c)

Histograms; bar graphs

d)

Histograms; pie charts

44.

Scatter plots and histograms are best used to visualize:

a)

. How a process or procedure is diagrammed

b)

How pieces of data compare within a data set

c)

How data changes over time

d)

How data is distributed

45.

scatter plots and histograms show how data is distributed while ____________ shows trends, or

how data changes over time.

a)

pie charts

b)

column charts

c)

flow charts

d)

line graphs

46.

How do scatter plots and histograms differ from line graphs?

a)

Scatter plots and histograms show how data is distributed while line graphs show trends,

or how data changes over time.

b)

Scatter plots and histograms show trends, or how data changes over time while line graphs

show how data is distributed.

c)

All three are used synonymously (mean the same thing)

d)

None of these

47.

. A _________________is the best way to display the percentage of employees that work in sales, marketing, and customer service at a large bank.

a)

scatterplot

b)

flow chart

c)

population pyramid

d)

pie chart

48.

A dietician is looking to help one of their clients, a professional athlete, with better eating

habits. They begin with a current breakdown of their client's diet by food group. Which of the

following options best visualizes this information?

a)

Pie chart

b)

Flow chart

c)

Column chart

d)

There is not enough information to make a determination

49.

Rate your understanding of Data Engineering.

a)

1* I am super lost

b)

2** I get some things but not others

c)

3*** I feel pretty good; I just need more practice

d)

4**** I feel super Confident

50.

________________ give a live view of changing data all in one place while __________________ pull specific trends and conclusions found in data that can explain the impact and outcome of data analysis

a)

Dashboards; reports

b)

Reports; dashboards

c)

Presentations; graphs

d)

Graphs; presentations

51.

Dashboards _______________ while reports ____________________.

a)

give a live view of changing data all in one place; pull specific trends and conclusions found

in data that can explain the impact and outcome of data analysis

b)

should be used when information is needed on a regular basis; should be used when

information is needed periodically

c)

Both answers

d)

neither answer

52.

Which of the following statements best describes dashboards and reports?

a)

Dashboards give a live view of changing data all in one place while reports pull specific

trends and conclusions found in data that can explain the impact and outcome of data

analysis.

b)

Dashboards should be used when information is needed on a regular basis while reports

should be used when information is needed periodically.

c)

. Dashboards display individual data points in a data set while reports can include some or

all data points in a data set.

d)

None of these

53.

What do data dashboards and reports have in common?

a)

They are both types of data reporting outputs.

b)

They both contain data visualization.

c)

both answers

d)

neither answers

54.

Which of the following data sets is best shown in a dashboard?

a)

A data set of the most common occupation by state in the United States

b)

A data set of current new job openings in the transportation industry

c)

A data set of the most purchased menu items at a restaurant

d)

all of these answers

55.

A data set of the least purchased menu items at a bakery is best shown as a _________________.

a)

Dashboard

b)

Report

c)

Memo

d)

None of these answers

56.

Which of the following is an example of information that is best shown as a report?

a)

A college counselor wants to know which universities have the highest acceptance rate

based on admissions data from last year

b)

Human resources wants to tell a business executive how happy their employees were this

month from open-ended survey results

c)

Both of these answers

d)

None of these answers

57.

The chance that something will happen is called ___________.

a)

statistics

b)

probability

c)

predictive analytics

d)

descriptive analytics

58.

Animal prints have become increasingly popular over the last 6 months. A fashion entrepreneur

decides to design an entire clothing line using animals as the theme. This is an example of

______________.

a)

a business identifying trends to better inform decision making

b)

a business identifying probabilities to better inform decision making

c)

a business identifying outliers to better inform decision making

d)

None of these

59.

Which ofthe following examples explain how data analysis can influence a business or

organization's decision making ability?

a)

A fashion entrepreneur noticing increased popularity in animal print clothing items over

the last 6 months and deciding to develop a clothing line around that theme.

b)

A non-profit director noticing a high rate of success with a fundraising campaign for small

eco-friendly companies and calculating the probability of a similar fundraising campaign

working well for those same eco-friendly companies.

c)

Both answers

d)

None of these answers

60.

Businesses and organizations can analyze data to identify _____________ and _______________that can result in better-informed decision-making.

a)

trends; probabilities

b)

trends; outliers

c)

probabilities; outliers

d)

probabilities; customer reviews

61.

Which ofthe following statements explain how data analysis can influence a business or

organization's decision making ability?

a)

. It can help determine trends, which could better inform decision makers

b)

It can help determine products or projects that are worth expanding based on the success

of a smaller project or product launch

c)

It can help determine the probabilities of events that influence the rate of success for a

project or product

d)

none of these

62.

Reports are best used to:

a)

tell an audience a story about data

b)

articulate high-level takeaways from a research study

c)

draw conclusions from the result of a project

d)

none of these

63.

Which of the following audiences is least likely to be interested in seeing data on a dashboard?

a)

A data scientist sharing real-time information with their colleagues

b)

A statistics professor demonstrating to their students how to gather and track data all in

one place

c)

An analyst detailing in-depth analysis of an ongoing project to their supervisor

d)

A fashion entrepreneur that researches other companies' sales before deciding on designs

for their next clothing line release.

64.

Rate your understanding of Data Engineering.

a)

1* I am super lost

b)

2** I get some things but not others

c)

3*** I feel pretty good; I just need more practice

d)

4**** I feel super Confident