What Is Your IQ On Data Science Techniques?

Reviewed by Editorial Team

The ProProfs editorial team is comprised of experienced subject matter experts. They've collectively created over 10,000 quizzes and lessons, serving over 100 million users. Our team includes in-house content moderators and subject matter experts, as well as a global network of rigorously trained contributors. All adhere to our comprehensive editorial guidelines, ensuring the delivery of high-quality content.

Learn about Our Editorial Process

| By Lynn Bradley

Lynn Bradley

Community Contributor

Quizzes Created: 319 | Total Attempts: 539,367

| Attempts: 494

Questions

Feedback

During the Quiz End of Quiz

Difficulty

Easy First Hard First Sequential

Share on Facebook Share on Twitter Share on Whatsapp Share on Pinterest Share on Email Copy to Clipboard Embed on your website

1/10 Questions

Classification is putting things in their best category.
- True
- False
- Hardly
- Sometimes

About This Quiz

Do you think you have the needed IQ for this quiz on Data Science Techniques? Scientists follow a particular pattern or techniques to get things done in the best possible way. Do you think you have the IQ to score beautifully well in this gorgeous and we'll write a quiz? Take this quiz and be amazed.

What Is Your IQ On Data Science TechnIQues? - Quiz

2.

Linear regression is used for variables?
- True
- False
- Maybe
- None of the above
Correct Answer

A. True

Explanation

Linear regression is used for variables because it is a statistical technique that is used to model the relationship between a dependent variable and one or more independent variables. It is commonly used to predict or estimate the value of the dependent variable based on the values of the independent variables. Therefore, linear regression is a suitable method for analyzing and understanding the relationship between variables.

Rate this question:
3.

Is the discriminant analysis a Technique?
- Yes
- No
- Complicated
- I don't know
Correct Answer

A. Yes

Explanation

Yes, discriminant analysis is a technique used in statistics and machine learning. It is a multivariate statistical method used to determine the differences or similarities between groups based on a set of predictor variables. It helps in classifying observations into different groups or categories based on their characteristics. Therefore, the correct answer is "Yes."

Rate this question:
4.

Statistical learning is accurately assessing the performance of a method.
- True
- False
- Partly true
- None of the above
Correct Answer

A. True

Explanation

Statistical learning involves accurately evaluating the performance of a method. This means that statistical learning is able to effectively assess how well a particular method or model is performing in terms of its predictions or outcomes. Therefore, the statement that "Statistical learning is accurately assessing the performance of a method" is true.

Rate this question:
5.

Which uses more than one independent variable in the linear regression?
- Simple
- Bi
- Multiple
- None of the above
Correct Answer

A. Multiple

Explanation

Multiple regression uses more than one independent variable in the linear regression model. In this type of regression, the relationship between the dependent variable and multiple independent variables is analyzed simultaneously. It allows for the examination of the individual effects of each independent variable on the dependent variable, while controlling for the effects of other variables. Therefore, the correct answer is "Multiple".

Rate this question:
6.

The techniques are the data which data scientist use in their day to day activities.
- True
- False
- Partly true
- I don't know
Correct Answer

A. True

Explanation

The statement is true because data scientists rely on various techniques in their daily work. These techniques include data collection, data cleaning, data analysis, data visualization, machine learning algorithms, statistical modeling, and more. By applying these techniques, data scientists are able to extract valuable insights and make data-driven decisions. Therefore, it can be concluded that the techniques are indeed used by data scientists in their day-to-day activities.

Rate this question:
7.

Which is not a type of linear regression?
- Simple linear regression
- Bi-linear regression
- Multiple linear regression
- None of the above
Correct Answer

A. Bi-linear regression

Explanation

Bi-linear regression is not a type of linear regression. Linear regression models the relationship between a dependent variable and one or more independent variables using a linear approach. Simple linear regression involves only one independent variable, while multiple linear regression involves more than one independent variable. However, bi-linear regression does not exist as a recognized type of linear regression.

Rate this question:
8.

What's is dichotomous?
- Binary
- Hexadecimal
- Two techniques
- None of the above
Correct Answer

A. Binary

Explanation

Dichotomous refers to something that is divided into two parts or has two distinct alternatives. In this context, binary is the correct answer because it is a system of numbering or representing information using only two digits, 0 and 1. Binary is commonly used in computer science and digital electronics, where data is represented using binary digits or bits. It is a fundamental concept in computing and forms the basis for all digital communication and computation.

Rate this question:
9.

What theorem does discriminant analysis use?
- Boyce's Law
- Pythagoras Theorem
- Bayee Theorem
- All of the above
Correct Answer

A. Bayee Theorem
10.

Which of these uses one independent variable?
- Bi-linear regression
- Multiple linear regression
- Latitude
- None of the above
Correct Answer

A. None of the above

Explanation

The given options are bi-linear regression, multiple linear regression, and latitude. Bi-linear regression and multiple linear regression both involve the use of multiple independent variables. Latitude, on the other hand, is not a statistical model and does not involve the use of any independent variables. Therefore, none of the given options uses only one independent variable.

Rate this question: