Important Questions for Data Analytics Using R

Valid for: BCA & Others/AU region and all other Andhra Pradesh universities

SUB: Data Analytics Using R

## UNIT 1: INTRODUCTION TO R PROGRAMMING

1. Define various data structures in R.

2. Mention about help functions in R? (Optional)

3. Features of R and history of R programming? (Optional)

4. Classify various operations on vectors in R.

5. What is the purpose of NA & NULL values in R give an example.

6. How to filter data in R give an example.

7. Mention various conditional statements in R with examples.

8. Define matrices and their operations in R with examples.

9. Define Lists and their operations in R with examples.

10. Define the data frame and their operations in R with examples

11. Define scalars and their types with examples.

12. How to apply a function to a List or Vector give an example.

13. Define function and its types with examples.

14. How to apply functions in a data frame with examples?

15. How to create a data frame in R give an example.

## UNIT 2: DATA FRAMES & PACKAGES IN R

1. Define the data frame and its operations with examples.

2. Describe about factors and tables in R.

3. Mention various control statements in R with examples.

4. Define looping statements in R with examples

5. Define packages in R and their need in programming.

6. Describe about tidyr and ggraph packages in R.

7. Describe about ggplot2 and dplyr package in R.

8. Describe about tidyquant and dygraphs package in R.

9. How to apply various functions to data frames in R.

10. Mention merging techniques in the data frame.

## UNIT 3A: INTRODUCTION TO DATA ANALYTICS

1. Define big data and its need in data analytics.

2. Mention various applications involved in data analytics.

3. Describe tools for data analytics (Optional)

4. Define the dataset and the Importance of big data.

## UNIT 3B: BASIC ANALYSIS TECHNIQUES

1. Define the Chi-Square test and give an example.

2. Define the t-test and give an example.

3. Define the Analysis of variance and give an example.

4. Define correlation and covariance with examples.

## UNIT 4: DATA ANALYSIS TECHNIQUES

1. Define regression and various types of regressions with examples.

2. Define linear regression with an example

3. Define various clustering techniques with examples.

4. Describe the Applications of R classification algorithm and classification techniques.

## UNIT 5: DATA VISUALIZATION USING R

1. Define data visualization and libraries used for data visualization in R.

2. Describe histograms, bar charts, and scatter plots with an example.

3. Describe about boxplot and heat map with an example.