# Intelligent Data Science And Analytics Assessment Test

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Cripstwick
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Quizzes Created: 693 | Total Attempts: 678,987
Questions: 10 | Attempts: 346  Settings  Although the two are different concepts, data science (or data driven science) and data analytics (or data analysis) are both focused on data. Take this quiz to find out more.

• 1.

### At what points do gradient descend methods converge?

• A.

Local minima

• B.

Optima minima

• C.

They don't converge

• D.

At point one

C. They don't converge
Explanation
Gradient descent methods do not always converge to a specific point. Instead, they continuously update the parameters in the direction of steepest descent until a stopping criterion is met. This means that the algorithm may stop at a local minimum or even a saddle point, rather than converging to the global minimum. Therefore, the correct answer is "They don't converge."

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• 2.

### The goal of _____ is to identify any changes to a web page that might increase outcome.

• A.

• B.

A/B testing

• C.

A/T testing

• D.

S/T testing

B. A/B testing
Explanation
A/B testing is a method used to compare two versions of a web page or advertisement to determine which one performs better in terms of achieving a desired outcome. By presenting different variations to a sample audience and analyzing their responses, any changes that lead to an improved outcome can be identified. This allows businesses to make data-driven decisions and optimize their web pages or ads for better results.

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• 3.

### Which of the following is used to understand linear transformation?

• A.

Eigenvector

• B.

Linear regression

• C.

Rectilinear

• D.

Eigenvalue

A. Eigenvector
Explanation
Eigenvectors are used to understand linear transformations. When a linear transformation is applied to an eigenvector, the resulting vector is parallel to the original eigenvector. Eigenvectors provide insight into the direction of the transformation and how it stretches or contracts space. By analyzing the eigenvalues associated with each eigenvector, we can determine the amount of stretching or contracting that occurs in each direction. Therefore, eigenvectors are a fundamental concept in understanding linear transformations.

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• 4.

### Which of these estimates gives prior knowledge about data?

• A.

Maximum likelihood estimates

• B.

Bayesian estimates

• C.

Prior estimates

• D.

Knowledge estimates

B. Bayesian estimates
Explanation
Bayesian estimates provide prior knowledge about the data. In Bayesian estimation, prior information or beliefs about the parameters of the data are incorporated into the analysis. This prior knowledge is combined with the observed data to obtain the posterior distribution, which represents the updated beliefs about the parameters. Therefore, Bayesian estimates take into account prior information, making them a suitable choice for incorporating existing knowledge into the analysis.

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• 5.

### Given the machine data and equation while it looks for the coefficient values in the equation is termed...

• A.

Artificial Intelligence

• B.

Machine Learning

• C.

Machine Language

• D.

Programming

B. Machine Learning
Explanation
The given question mentions that the machine data and equation are used to find the coefficient values in the equation. This process of using data and equations to learn and make predictions is a characteristic of Machine Learning. Machine Learning algorithms are designed to analyze data, learn patterns, and make predictions or decisions without being explicitly programmed. Therefore, the correct answer is Machine Learning.

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• 6.

### Why is Python preferable for text analytics over R?

• A.

It is easier to learn

• B.

It has libraries

• C.

It uses data

• D.

It is marked up

B. It has libraries
Explanation
Python is preferable for text analytics over R because it has a wide range of libraries specifically designed for text analysis tasks. These libraries, such as NLTK, spaCy, and TextBlob, provide ready-to-use functions and tools for tasks like tokenization, stemming, sentiment analysis, and named entity recognition. These libraries save time and effort for developers and researchers, allowing them to focus on the analysis itself rather than building the necessary tools from scratch. Additionally, Python's libraries are constantly updated and improved by a large community, ensuring that users have access to the latest advancements in text analytics.

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• 7.

### Which of these is widely used for mining classifying datasets?

• A.

Logistical regression

• B.

Classification technique

• C.

Recommender systems

• D.

Data merging

B. Classification technique
Explanation
Classification technique is widely used for mining classifying datasets. It is a method of categorizing data into different classes or groups based on their characteristics. This technique helps in organizing and analyzing large amounts of data by assigning labels or categories to each data point. It is commonly used in various fields such as machine learning, data mining, and pattern recognition to make predictions and decisions based on the given dataset.

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• 8.

### Which of the following is a statistical technique in which the value of a variable A is predicted from the value of a second variable B?

• A.

Interpolation

• B.

Extrapolation

• C.

Linear regression

• D.

Rectilinear regression

C. Linear regression
Explanation
Linear regression is a statistical technique used to predict the value of one variable (A) based on the value of another variable (B). It assumes a linear relationship between the two variables and calculates the best-fit line that minimizes the distance between the observed data points and the predicted values. This technique is commonly used in various fields, such as economics, social sciences, and finance, to analyze and predict the relationship between variables.

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• 9.

### When you are estimating a value from two values, you're...

• A.

Extrapolating

• B.

Interpolating

• C.

Extracting

• D.

Collecting

B. Interpolating
Explanation
When you are estimating a value from two known values, you are interpolating. Interpolation involves using the known data points to estimate or predict an intermediate value within the range of those points. It is a method of estimating values within a range based on the relationship between the known values.

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• 10.

### The point in a data distribution where there is no bias to the left nor to the right is called...

• A.

Central distribution

• B.

Normal distribution

• C.

Central tendency

• D.

Normal deviation Back to top