Data analysis is an important concept which deals with analyzing the data and extract useful insights from it. Data Analysts, Data Scientists, Data Engineers and other data professionals often deal with huge amount of data daily to help companies make significant use of their data and derive useful decisions. This data analysis quiz or data analytics quiz focus is to provide you with a resource to test and quantify your data analysis skills.

In this text, we will provide you an online data analysis quiz and test on data analysis basic and fundamental concepts knowledge. This quiz is based on data analysis questions and will test you on your basic and intermediate data analysis knowledge and understanding of its concepts.

👉 You may also like: What is Data Analytics and its types?

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Data Analysis Quiz

In today’s world, proper utilization of data is very crucial and essential for any organisation, company or a business. Data analysis is the process of collecting, analyzing, updating, and visualizing data in order to derive useful insights, which in-turn help companies to make better data driven decisions.

These decisions help them in making future business plans, better targeting to potential customers, which locations are good for their future growth (where to sell their product or services) and helps them in lowering the marketing, sales and other costs.

Data analysts, data scientists, data engineers, data architects and other data professionals help organisations to achieve these results. Thus the demand of these professionals are very high as compared to other professionals.

How it helps?

Companies want to hire skilled and expert data professionals. And, data professionals would like to stay updated and test their data analysis skills to get hired in their dream job!

This data analysis quizlet or data analysis skills test helps data analysts, data scientists and other data professionals to test their knowledge on the basics and fundamental concepts of data analysis. Which can help them in preparing for their data analyst, data scientist or data engineer jobs interview.

For the companies, recruiters and recruitment agencies these online quizzes and tests help them to evaluate and recruit the right candidates based on their data analysis skills and knowledge.

Companies through these quizzes can judge the potential of candidates on their basic, intermediate and advance knowledge on data analysis skills, topics and their ability to extract useful actionable plans, insights, which can help companies in achieving their targets.

Data Analysis Quiz: Basic and Intermediate Level Questions

This data analytics quiz, data analyst quiz, data science quiz or data engineer quiz is based on data analytics test questions. It will help in evaluating candidates knowledge and skill levels through basic and intermediate difficulty level questions.

This data analysis questions examples can also help professionals, who are looking to prepare for their data analyst or data scientist interviews with the mock test on essential capabilities and skills required for data analysis.

Data Analysis Quiz Topics:

Following are some of the topics covered in this quiz:

• Data analysis basic understanding and fundamental concepts like mean, median, range, exploratory data analysis (EDA) and more;
• What are the types of data, knowledge of different structures of data, variables etc.
• What are Descriptive Statistics used for analyzing data and Measures of Central Tendency?
• Ways to identify and apply statistical techniques;
• What is Inferential Statistics and Hypothesis Testing;
• Skills of understanding and interpreting data;
• Examples of data analysis;
• Understanding of data visualization concepts for data analytics.

Evaluation Criteria: Quiz Score Categories

The evaluation criteria of this data analysis quiz is based on the scores a candidate achieve. Here are some of the assumptions:

1. Score < 75% (Fail): If your quiz overall score would be less than 75%, it shows you may lack a solid understanding of basic data analysis concepts. It means you or the candidate may require additional study or training in foundational data analysis concepts.
2. If you score between 75% to 90% (Pass): Score between 75% to 90% shows a satisfactory understanding of basic data analysis concepts. Candidate may have performed well overall but there may be some areas where they could improve or gain a deeper understanding.
3. And, if you achieve score more than 90% (High Pass): That indicates a candidate have a strong understanding and proficiency in fundamental data analysis concepts. Which means a candidate can apply data analysis concepts effectively.

If a candidate falls under category 1 or 2, we advise them to prepare more and take this quiz again to testify their skills.

And, if a candidate comes under category 3, we recommend them to take more advance quizzes and tests or data analysis quiz on more specific topics to further evaluate their eligibility. We will keep on adding these, so stay connected!

So, let’s start taking the quiz now!

Data Analysis Quiz on Basic and Fundamental Concepts

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Hi , click on Start button below to start the Data Analysis Quiz.

Quiz consists of 20 questions. You will get 10 minutes to complete this quiz.
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Data Analysis Basics Quiz on Intermediate Level Questions

Data Analysis Quiz

This quiz can help the data professionals to test their data analysis skills for its basics and fundamental concepts.

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1 / 20

Category: Data Analysis Basics Quiz on Intermediate Level Questions

1. What is Data Analysis?

1. Data analysis is the process of collecting data from various sources

2. It is the process of organizing data in spreadsheets

3. It is the process of examining, cleaning, transforming, and interpreting data

4. It is the process of visualizing data using charts and graphs

Your answer was incorrect.

Your answer was correct.

Data analysis is the process of systematic examination, cleaning, transformation, and interpretation of data to uncover patterns, trends, and relationships. Although, collecting and organizing data are important steps in the data analysis process, data analysis itself involves much more than just these initial stages.

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Category: Data Analysis Basics Quiz on Intermediate Level Questions

2. What is an outlier in data analysis?

1. A data point that falls within the normal range of the distribution.

2. A data point that significantly deviates or different from the majority of the data.

3. The data point that appears most frequently.

4. The average of all values in the dataset.

Your answer was incorrect.

Your answer was correct.

An outlier is a data point that is statistically far or different from the rest of the data points. That may have happened due to incorrectly capturing the data or because of any unusual circumstances.

3 / 20

Category: Data Analysis Basics Quiz on Intermediate Level Questions

3. What is the importance of data quality in data analysis?

1. Data quality doesn't significantly impact the results.

2. High-quality data leads to more reliable and accurate analysis results.

3. Data quality only matters for complex statistical models.

4. Data quality is only important for data visualization.

Your answer was incorrect.

Your answer was correct.

"Garbage in, garbage out" applies to data analysis. Good quality data (accurate, consistent, complete) is essential for reliable and trustworthy results.

4 / 20

Category: Data Analysis Basics Quiz on Intermediate Level Questions

4. What is the difference between "population" and "sample" in data analysis?

1. The population refers to the entire set of individuals or objects under study, while the sample is a subset of the population selected for analysis.

2. The population is a statistical measure, while the sample is a graphical representation of data.

3. The population consists of qualitative data, while the sample consists of quantitative data.

4. The population is used for descriptive statistics, while the sample is used for inferential statistics.

Your answer was incorrect.

Your answer was correct.

In data analysis, the "population" refers to the entire group of individuals or objects that are of interest to the researcher or on which the study is conducted. It represents the complete set of observations (data) that is surveyed. On the other hand, a "sample" is a subset of the population that is selected for analysis. The sample is chosen in such a way that it is representative of the population as a whole.

5 / 20

Category: Data Analysis Basics Quiz on Intermediate Level Questions

5. What does the mode represent in a data set?

1. The most frequently occurring value

2. The average of the data set

3. The middle value of the data set

4. The spread of the data set

Your answer was incorrect.

Your answer was correct.

Mode is that value in a dataset that appears highest or most number of times.

6 / 20

Category: Data Analysis Basics Quiz on Intermediate Level Questions

6. What does a standard deviation tell you about a dataset?

1. The most frequent value in a dataset.

2. The spread of data points around the mean.

3. The relationship between two variables.

4. Whether the data is skewed.

Your answer was incorrect.

Your answer was correct.

Standard deviation tells how close data points are clustered around the mean of a dataset.

7 / 20

Category: Data Analysis Basics Quiz on Intermediate Level Questions

7. What is the range of the following data set: 10, 15, 20, 25, 30?

1. 5

2. 20

3. 25

4. 15

Your answer was incorrect.

Your answer was correct.

The range is the difference between the maximum and minimum values in a data set. In this case, the range is 30 - 10 = 20.

8 / 20

Category: Data Analysis Basics Quiz on Intermediate Level Questions

8. What is the median of the following data set: 5, 10, 15, 20, 25?

1. 10

2. 15

3. 20

4. 12.5

Your answer was incorrect.

Your answer was correct.

The median is the middle value of a data set when arranged in ascending order. In this case, the middle value is 15.

9 / 20

Category: Data Analysis Basics Quiz on Intermediate Level Questions

9. Which of the following is a categorical variable?

1. Age

2. Height

3. Gender

4. Weight

Your answer was incorrect.

Your answer was correct.

Categorical variables represent categories or groups and can take only a limited number of values. Thus, Gender (e.g., male, female) is an example of a categorical variable.

10 / 20

Category: Data Analysis Basics Quiz on Intermediate Level Questions

10. What is the main purpose of exploratory data analysis (EDA)?

1. To predict future outcomes

2. To summarize and visualize data for preliminary insights

3. To perform hypothesis testing

4. To build predictive models

Your answer was incorrect.

Your answer was correct.

Exploratory data analysis (EDA) is the process of examining and visualizing data sets to summarize their main characteristics. It is performed with the goal of generating hypotheses or making initial assessments before formal modeling or start building predictive models.

11 / 20

Category: Data Analysis Basics Quiz on Intermediate Level Questions

11. Which type of data is represented by a bar chart?

1. Continuous data

2. Categorical data

3. Ordinal data

4. Nominal data

Your answer was incorrect.

Your answer was correct.

Bar charts are used to represent categorical data, where the bars represent different categories or groups.

12 / 20

Category: Data Analysis Basics Quiz on Intermediate Level Questions

12. What is the difference between "descriptive statistics" and "inferential statistics"?

1. Descriptive statistics summarize the data, whereas inferential statistics make predictions about populations.

2. Descriptive statistics use charts, inferential statistics use numbers.

3. Descriptive statistics deal with large datasets, inferential statistics deal with small datasets.

4. There's no difference, they mean the same thing.

Your answer was incorrect.

Your answer was correct.

Descriptive statistics describe the properties of a dataset (mean, median, etc.), while inferential statistics use sample data to draw conclusions about the larger population (hypothesis testing).

13 / 20

Category: Data Analysis Basics Quiz on Intermediate Level Questions

13. What is the difference between "precision" and "recall" in data analysis?

1. Precision refers to true positives, recall refers to all positives (including false positives)

2. Precision refers to the number of data points, recall refers to the percentage of relevant data captured

3. Precision refers to trends, recall refers to central tendency

4. These terms are interchangeable

Your answer was incorrect.

Your answer was correct.

Precision is the measure of actual positives out of total identified positives. Whereas, recall measures the proportion of all positive values captured while analysing the data.

14 / 20

Category: Data Analysis Basics Quiz on Intermediate Level Questions

14. When interpreting a correlation coefficient, a value closer to 1 indicates?

1. No relationship between the variables.

2. A strong positive relationship between the variables.

3. A weak positive relationship between the variables.

4. A negative relationship between the variables.

Your answer was incorrect.

Your answer was correct.

Correlation coefficient values range from -1 (perfect negative correlation) to +1 (perfect positive correlation), with 0 indicating no linear relationship and 1 indicates a strong positive relationship between the variables.

15 / 20

Category: Data Analysis Basics Quiz on Intermediate Level Questions

15. What is the primary goal of data visualization in data analysis?

1. To perform complex statistical calculations on data.

2. To clearly communicate trends, patterns, and insights from data.

3. To store and manage large datasets efficiently.

4. To clean and prepare data for analysis.

Your answer was incorrect.

Your answer was correct.

Data visualization is a process of translating complex data into easy-to-understand charts, graphs and dashboards to understand the data and communicate findings or insights in an easy and effective way.

16 / 20

Category: Data Analysis Basics Quiz on Intermediate Level Questions

16. What does a histogram visualize?

1. Relationship between two variables.

2. Distribution of a single variable data points throughout the data.

3. Time series data.

4. Location or Geographic data.

Your answer was incorrect.

Your answer was correct.

A histogram is used to visualize the distribution of a single variable by dividing the data into bins and representing the frequency or count of observations in each bin.

17 / 20

Category: Data Analysis Basics Quiz on Intermediate Level Questions

17. If a boxplot visualization shows a clear outlier in a dataset. What is the most appropriate course of action?

1. Ignore the outlier as it likely has minimal impact.

2. Automatically remove the outlier without investigation.

3. Investigate the outlier to determine if there's a genuine reason for its deviation.

4. Exclude the outlier only if it significantly affects the calculated mean.

Your answer was incorrect.

Your answer was correct.

Outliers can be genuine data points or indicate errors. It is essential to understand and analyze the outliers impact on the data, you are working on. After that decide, what to do with outlier values either to delete it or treat it or keep it.

18 / 20

Category: Data Analysis Basics Quiz on Intermediate Level Questions

18. What is the purpose of a scatter plot in data analysis?

1. To visualize the distribution of categorical data.

2. To display the relationship between two continuous variables.

3. To summarize the central tendency of a data set.

4. To compare the frequencies of different categories in a data set.

Your answer was incorrect.

Your answer was correct.

A scatter plot is a graphical representation used to visualize the relationship between two continuous variables.

19 / 20

Category: Data Analysis Basics Quiz on Intermediate Level Questions

19. Which of the following is a measure of variability in a data set?

1. Mean

2. Median

3. Standard deviation

4. Mode

Your answer was incorrect.

Your answer was correct.

Standard deviation measures the spread or variability of data points around the mean. It indicates how much the values in a data set deviate from the mean.

20 / 20

Category: Data Analysis Basics Quiz on Intermediate Level Questions

20. What does the p-value represent in hypothesis testing?

1. The probability of committing a Type I error

2. The probability of committing a Type II error

3. The level of significance

4. The probability of observing the test statistic or more extreme results under the null hypothesis

Your answer was incorrect.

Your answer was correct.

The p-value is the probability of observing the test statistic or more extreme results if the null hypothesis is true. P value helps in determining the strength of evidence against the null hypothesis.

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The average score is 78%

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Conclusion

The above data analysis quiz is specifically designed for the professionals who are either beginners or experienced and looking to build or enhance their career in the field of data analysis.

Stay connected with us and explore this space, as we will cover more online quizzes, tests and assessments to help you in testing, validating and gaining job skills for a successful career.

Happy Quizzing and Learning!