R Programming Quiz: Trivia Exam!

1. What does OLS stand for?

Office of Legislative Services

Ottawa Linux Symposium

Organizational Leadership Supervision

Ordinary Least Squares

D

Explanation

D

2. What does EDA mean?

Electronic design automation

Economic development administration

Exploratory data analysis

Electronic data access

C

Explanation

C

3. Function unlist() is used for

Convert a list into vector

Convert a vector into list

Convert a categorical data into numeric

List of the variables defined

A

Explanation

A

4. Which of the following is most sensitive to outliers?

K-means clustering

K-medians clustering

K-modes clustering

K-medoids clustering

A

Explanation

A

5. The correlation coefficient (r) is used to determine:

A specific value of the y-variable given a specific value of the x-variable

A specific value of the x-variable given a specific value of the y-variable

The strength of the relationship between the x and y variables

None of these

C

Explanation

C

6. The most commonly used measure of similarity is

Euclidean distance

Ward.d2 distance

Chebychev’s distance

Manhattan distance

A

Explanation

A

7. What is the function used for building linear regression model?

Glm()

Lm()

Linear()

Slm()

B

Explanation

B

8. Values which are measured in terms such as weight, height, length are called as?

Continuous variables

Measuring variables

Flowchart variables

Discrete variables

A

Explanation

A

9. The function var() in R results

Sample variance

Population variance

Sample standard deviation

Population standard deviation

A

Explanation

A

10. Quadratic regression model equation is

Y = B0 + B1X + B2Y^2 + e

Y = B0 + B1Log(X) + e

Y = B0 + B1X + B2X^2 + e

Y^2 = B0 + B1X + e

C

Explanation

C

11. What does table() function tell us about a data frame

Probability distribution

Normal distribution

Z value

Frequency distribution

D

Explanation

D

12. What are heterogeneous data structures among these in R?1. Vector 2. Matrix 3. List 4. Data frame 5. Factor

1, 2

1, 3, 4

3, 4

1, 2, 3

C

Explanation

C

13. Effect of an outlier on the value of a correlation coefficient (r)

It will always decrease correlation coefficient

It will always increase correlation coefficient

It might either decrease or increase a correlation coefficient, depending on its relation with other points

It will have no effect on the correlation coefficient

C

Explanation

C

14. The least squares estimator in MLR is derived by

Minimizing the sum of squared errors

Making the sum of squared errors equal to one

Minimizing the absolute difference of the residuals

Forcing the smallest distance between the actual and fitted values

A

Explanation

A

15. Correlation and regression, these two measures:

The relationship between two categorical variables

The relationship between two quantitative variables

He relationship between a quantitative input variable and a categorical output variable

The relationship between a categorical input and a quantitative output variable

B

Explanation

B

16. The intercept/constant in the regression model

Tells about the height of the regression line

Tells about the slope of the line

Should be excluded if one variable has negative values

Is statistically significant if it is larger than 1.96

A

Explanation

A

17. How to visualize data in Pie Chart?

Pie

Pieplot

Pipe

Package

A

Explanation

A

18. What are homogeneous data structures among these in R?1. Vector 2. Matrix 3. Array 4. Data frame 5. Factor

1, 2

1, 3, 4

3, 4, 5

1, 2, 3

D

Explanation

D

19. The method of analysis which does not classify variables as dependent or independent?

Regression analysis

Discriminant analysis

Analysis of variance

Cluster analysis

D

Explanation

D

20. Which of the following clustering requires merging approach?

Partitional

Hierarchical

Knn

PCA

B

Explanation

B

21. Measure the probability of an output which is binary?

Lm()

Knn()

Glm()

Mean()

C

Explanation

C

22. Which data structure is used to store categorical variables?

Data frame

Factor

Integer

Categorical

B

Explanation

B

23. Z value at 99% confidence levels

2.015

2.575

1.960

1.645

B

Explanation

B

24. K-Mean Clustering can be explained by1. Adjust number of iterations2. Find out the optimal number of clusters3. K-means is sensitive to initializations of cluster centers4. Bad initialization can lead to Poor clustering

1, 2 and 3

1 and 3

1 and 2

All the above

D

Explanation

D

25. Finding dissimilarity between two clusters in hierarchical clustering can be done by?1. Single-link 2. Complete-link 3. Average-link

1 and 2

1 and 3

2 and 3

1, 2 and 3

D

Explanation

D

26. What is the memory limit in R?

1TB

2TB

5TB

8TB

D

Explanation

D

27. A statement which is not true about clustering:

Clustering is used for analyzing data when the dependent variable is categorical and the independent variables are discrete

Clustering is also called classification analysis

Groups or clusters are suggested by the data

Objects in each cluster tend to be similar to each other and dissimilar to objects in the other clusters

A

Explanation

A

28. What does mode() function do?

1st-moment business decision

Data type

Storage mode

Data frame

C

Explanation

C

29. The data mining technique involved in predicting a categorical response is called as?

Regression

Classification

Clustering

Summarization

B

Explanation

B

30. The regression equation _______________, when the coefficient of determination is a positive value

Will have a positive slope

Will have a negative slope

Will have a positive y intercept

Could have either a positive or a negative slope

D

Explanation

D

31. What is the function used for scatterplot for all the pairs of a dataset?

Cor()

Plot()

Scatter()

Pairs()

D

Explanation

D

32. What if a number and an NA value concatenate together, what will the resulting structure be?

Character

Number

Factor

List

B

Explanation

B

33. Technique used to find the best choice of number of clusters

Scree plot

Knn

Skewness

Dendrogram

A

Explanation

A

34. What is the function used to read CSV files into R?

Csv()

Read.csv()

Read_csv()

B & c

D

Explanation

D

35. What is the result of Hierarchical Clustering?

Estimate of cluster centroids

Tree showing relations between each other

Assignment of each point to clusters

All of the Mentioned

B

Explanation

B

36. The minimum number of variables required for clustering exercise?

0

1

2

3

B

Explanation

B

37. The interpretation of the slope coefficient in the model y = B0 + B1X + e is?

1% change in X is associated with a B1 % change in Y

Change in X by one unit is associated with a B1 change in Y

Change in X by one unit is associated with a 100 B1 % change in Y

1% change in X is associated with a change in Y of 0.01 B1

In the linear regression model y = B0 + B1X + e, B1 represents the slope coefficient. This coefficient quantifies the relationship between the independent variable (X) and the dependent variable (Y). Specifically, it indicates the change in Y for a one-unit change in X. For instance, if B1 is 2, then for every one-unit increase in X, Y is predicted to increase by 2 units. The slope coefficient is crucial in understanding the magnitude and direction of the linear relationship between the variables.

Explanation

In the linear regression model y = B0 + B1X + e, B1 represents the slope coefficient. This coefficient quantifies the relationship between the independent variable (X) and the dependent variable (Y). Specifically, it indicates the change in Y for a one-unit change in X. For instance, if B1 is 2, then for every one-unit increase in X, Y is predicted to increase by 2 units. The slope coefficient is crucial in understanding the magnitude and direction of the linear relationship between the variables.

38. If the coefficient of determination (R^2) is equal to 1, then the correlation coefficient (r)

Is also equal to 1

Lie between -1 or +1

Be either of -1 to +1

Must be -1

The coefficient of determination (R^2) represents the proportion of the variance in the dependent variable that is predictable from the independent variable. It ranges from 0 to 1. The correlation coefficient (r) measures the strength and direction of the linear relationship between two variables, ranging from -1 to +1. When R^2 = 1, it signifies a perfect linear association between the variables, implying that all data points fall perfectly on a straight line. This perfect linear relationship can be either positive (r = +1) or negative (r = -1)

Explanation

The coefficient of determination (R^2) represents the proportion of the variance in the dependent variable that is predictable from the independent variable. It ranges from 0 to 1. The correlation coefficient (r) measures the strength and direction of the linear relationship between two variables, ranging from -1 to +1. When R^2 = 1, it signifies a perfect linear association between the variables, implying that all data points fall perfectly on a straight line. This perfect linear relationship can be either positive (r = +1) or negative (r = -1)