# Data Science Objective Set 1

Which of the following is not considered a cause of confusion about the precise meaning of the data science buzzwords?

The constant evolution of the data science industry and in turn the meaning of the data science buzzwords

Ans:-The speed with which new data science terms are appearing

Which of the following is related to the meaning of the term analytics?

Analytics is about separating a dataset into easy-to-digest chunks and studying them individually and examine how they relate to other parts

Ans:-Analytics is the application of logical and computational reasoning to the component parts obtained in an analysis

Which of the terms relates to the field of business analytics only?

Creating dashboards

Reporting with visuals

Ans:- Qualitative analytics

Which of the following is not considered a data analytics activity?

Ans:-Business case studies

Preliminary data reporting

Optimization of drilling operations

Which of the following is considered data science?

Business case studies

Qualitative analytics

Digital signal processing

Sales forecasting

Given that all activities can be done with ML and all can be done without ML, choose the best answer. Which of the following is considered Data science but not Machine learning?

Creating real-time dashboards

Ans:-Sales forecasting

Fraud prevention

Which of the following is not an example of where Machine Learning is being applied today?

Ans:-Symbolic reasoning

Client retention

Image recognition

From a data scientist’s perspective, the solution of every task begins:

by suggesting a few hypothetical and theoretical solutions to your boss

by gathering your team and deciding on what approach to follow to solve the task

Ans:-with a proper dataset

According to our infographic, which of the following is not considered data science?

Ans:-Big data

Business intelligence

Traditional data science methods

Which of the following is related to the pre-processing of a traditional data set?

Class labelling

Data cleansing

Dealing with missing values

Ans:-All of the above

Which of the following do you encounter when working with big data?

Text data

Integer

Digital image data

Ans:-All of the above

The process of representing observations as numbers is called:

Collecting observations

Ans:-Quantification

A measure that has a business meaning attached is called:

an observation

a quantification

Ans:-a metric

A KPI (Key Performance Indicator) can be best defined as:

the accumulation of observations to show some information

Ans:-a metric that is tightly aligned with your business objectives

a quantification that has a business meaning attached

an observation that can potentially be related to the business goals of a company

The job of a business intelligence analyst always involves the creation of:

reports

dashboards

KPIs

Ans:-All of the above

Which of the following columns from our infographic contain activities that are said to belong to the field of ‘predictive analytics’ and do not aim at explaining past behaviour?

Traditional data

Big data

Business intelligence

Ans:-Traditional methods

In business and statistics, which is the general term that refers to using a model for quantifying causal relationships?

Ans:-regression analysis

factor analysis

cluster analysis

time-series analysis

Which technique can be implemented if you want to reduce the dimensionality of a certain statistical problem?

Ans:-factor analysis

cluster analysis

time-series analysis

all of the above

Which technique is associated with plotting values against time, shown always on the horizontal line?

regression analysis

Ans:-time-series analysis

factor analysis

cluster analysis

When the data is divided into a few groups, you should apply:

factor analysis

Ans:-cluster analysis

time-series analysis

Which of the following statements is true?

The core of machine learning is creating an algorithm, which a computer then uses to find a model that fits the data as best as possible

In machine learning, one does not give the machine instructions on how to find a model. Rather, one provides it with algorithms which give the machine directions on how to learn on its own

A machine learning algorithm is like a trial-and-error process, but the special thing about it, is that each consecutive trial is at least as good as the previous one

Ans:-All of the above

Which line represents the four ingredients of any machine learning algorithm?

Model, data, reward system, objective function

Ans:-Data, model, objective function, optimization algorithm

Model, labelled data, unlabelled data, optimization algorithm

Choose the best answer.

In which type of machine learning is one always working with unlabelled data?

Supervised learning

Ans:-Unsupervised learning

Reinforcement learning

In reinforcement learning, a reward system is being used to improve the machine learning model at hand. The idea of using this reward system is to:

to minimize the error of the model

to minimize the objective function

Ans:-to maximize the objective function

to improve the optimization algorithm