Visualization Case Study: Concrete Strength

Visualization Case Study: Concrete Strength

Assessment

Interactive Video

Created by

Quizizz Content

Information Technology (IT), Architecture, Engineering, Social Studies

12th Grade - University

Hard

The video tutorial covers data visualization and exploration using a concrete strength data set. It begins with an introduction to the case study and data set, followed by creating one-dimensional plots to analyze data distributions. The tutorial then explores two-dimensional plots to identify correlations and moves on to multidimensional plots and principal component analysis (PCA) for data reduction. Finally, it discusses advanced plotting techniques using tools like Plotly and pandas profiling.

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10 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the primary goal of the concrete strength case study?

To find the cheapest concrete materials

To predict concrete compressive strength

To determine the best concrete mixture

To visualize the color of concrete

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following is NOT an input feature for predicting concrete strength?

Cement

Water

Color of concrete

Age of concrete

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What type of plot is useful for visualizing the distribution of a single feature?

Scatter plot

Line plot

Violin plot

Heat map

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does a violin plot combine?

Bar chart and pie chart

Heat map and histogram

Box plot and density plot

Scatter plot and line plot

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which plot is particularly useful for showing correlations between two features?

Box plot

Histogram

Scatter plot

Violin plot

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does a heat map show in data visualization?

The distribution of a single feature

The correlation between features

The maximum and minimum values

The average value of features

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of principal component analysis (PCA)?

To calculate the mean of features

To visualize data in 2D

To reduce data dimensionality

To increase the number of features

8.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

In a 3D scatter plot, what can be varied to represent different data attributes?

Length and depth

Height and width

Shape and texture

Color and size

9.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a key feature of Plotly in data visualization?

It creates static plots

It only works with 2D data

It allows interactive exploration

It requires no coding

10.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does pandas profiling provide in data analysis?

A summary of data distributions

A tool for data encryption

A method for data cleaning

A way to visualize data in 3D

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