PCED-30-01 Certified Entry-Level Data Analyst with Python Exam Free Dumps

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dumps Python Institute Certified Entry-Level Data Analyst with Python PCED-30-01 exam, PCED-30-01 exam dumps

PCED-30-01 Certified Entry-Level Data Analyst with Python exam is easy to take now. There are 45 Single- and multiple-select questions in real PCED-30-01 exam, and you have 60 minutes to answer all the questions. The passing score is 75%. The available language is English. The exam cost is $69, and $86 (exam and retake). We have cracked the latest Certified Entry-Level Data Analyst with Python PCED-30-01 exam dumps, which can ensure you pass the test easily. Free Certified Entry-Level Data Analyst with Python PCED-30-01 exam dumps are available below.

Page 1 of 8

1. In the context of data acquisition, what does ETL stand for?

Extract, Transform, Load

Extract, Transfer, Load

Edit, Transform, Load

Enhance, Transform, Load

2. Which of the following is NOT a commonly used data acquisition method?

Web scraping

API integration

Data visualization

Manual data entry

3. What is the purpose of data pre-processing in a data analytics workflow?

To make the data more difficult to analyze

To remove noise and irrelevant information

To increase the computational complexity

To slow down the data analysis process

4. Which of the following techniques can be used in data pre-processing to handle missing values?

Removing rows with missing values

Replacing missing values with the mean of the column

Ignoring missing values altogether

Filling missing values with zeros

5. What is outlier detection in the context of data pre-processing?

Identifying extreme values or anomalies in the data

Highlighting positive trends in the data

Analyzing data to predict future outcomes

Sorting data based on a predefined criteria

6. Which of the following is NOT an example of data cleaning in the pre-processing stage?

Removing duplicate entries

Converting categorical data to numerical values

Handling missing values

Aggregating data from multiple sources without validation

7. Why is data normalization important in data pre-processing?

It helps in increasing the size of the dataset

It ensures that all features have the same scale

It makes the data difficult to interpret

It slows down the data analysis process

8. Which of the following techniques can be used in data pre-processing for feature selection?

Principal Component Analysis (PCA)

Support Vector Machines (SVM)

k-Nearest Neighbors (k-NN)

Linear Regression

9. What does the "len()" function in Python do?

Returns the sum of all elements in a list

Returns the average of elements in a list

Returns the number of elements in a list

Returns the maximum value in a list

10. What is the correct way to comment a single line of code in Python?

// This is a comment

/* This is a comment */

# This is a comment

Page 2 of 8

11. Which of the following is used to perform integer division in Python?

12. What is the output of the following code snippet? ```python x = 5 y = 2 print(x ** y) ```

13. Which of the following is not a valid variable name in Python?

my_var

myVar

1_var

_var

14. What does the "range()" function in Python do?

Generates a list of numbers

Filters elements in a list

Returns the length of a list

Reverses the order of elements in a list

15. What is the main purpose of statistical analysis in data analytics?

To organize data

To visualize data

To draw conclusions from data

To collect data

16. Which measure of central tendency is affected by outliers?

Mean

Median

Mode

Range

17. When is the mode the most appropriate measure of central tendency to use?

When the data is normally distributed

When the data has outliers

When the data is skewed

When the data is categorical

18. What does skewness measure in a data distribution?

Spread of the data

Symmetry of the data

Deviation from the mean

Kurtosis of the data

19. Which statistical test is used to determine if there is a significant difference between the means of two independent groups?

T-test

ANOVA

Chi-square test

Regression analysis

20. What is the p-value in hypothesis testing?

The probability of making a Type I error

The probability of making a Type II error

The level of significance

The probability of observing the test statistic

Page 3 of 8

21. Which type of correlation coefficient indicates a strong positive linear relationship between two variables?

-1.0

1.0

0.5

0.0

22. What is the purpose of regression analysis in statistical analysis?

To summarize the data

To determine cause and effect relationships

To identify trends over time

To calculate probabilities

23. What is the purpose of data analysis in the context of a Python programming for data analytics?

To collect data

To visualize data

To interpret data

To delete data

24. Which of the following Python libraries is commonly used for data analysis and modeling?

TensorFlow

Matplotlib

NumPy

Django

25. What is the goal of data modeling in the field of data analytics?

To organize data

To analyze data

To make predictions based on data

To clean data

26. In data analytics, what does the term "feature engineering" refer to?

Creating new features from existing data

Removing features from the dataset

Engineering the physical features of the data

Analyzing features in detail

27. Which technique is commonly used in machine learning for splitting a dataset into training and testing sets?

Randomization

Normalization

One-hot encoding

Train-test split

28. What is the process of evaluating a model's performance using data that the model has not seen during training known as?

Model validation

Model training

Model testing

Model optimization

29. Which of the following metrics is commonly used to evaluate classification models in data analytics?

Mean Squared Error

Receiver Operating Characteristic (ROC) curve

R-squared

Accuracy

30. What is the process of fine-tuning a machine learning model to improve its performance known as?

Model validation

Hyperparameter tuning

Data preprocessing

Feature selection

Page 4 of 8

31. Which of the following libraries in Python is commonly used for data visualization?

numpy

pandas

matplotlib

scikit-learn

32. What type of plot would be most suitable for showing the distribution of a single numerical variable?

Scatter plot

Bar plot

Histogram

Box plot

33. Which function in pandas is used to create a line plot from a DataFrame?

plot()

scatter()

boxplot()

hist()

34. In a line plot, what do the points connected by a line represent?

Mean values

Median values

Maximum values

Sequential data points

35. Which of the following is an advantage of using seaborn for data visualization in Python?

Limited customization options

High-level interface for creating attractive plots

Slow rendering speed

Limited compatibility with other libraries

36. What type of plot would be most suitable for comparing the distribution of a numerical variable across different categories?

Scatter plot

Pie chart

Box plot

Bar plot

37. Which of the following is an advantage of using interactive plots for data visualization?

Limited user engagement

Ability to zoom, pan, and interact with data

Fixed visual display

Slow rendering speed

38. What type of plot is commonly used to visualize the relationship between two numerical variables?

Box plot

Scatter plot

Histogram

Pie chart

39. What is the purpose of data acquisition in data analytics?

Storing data

Cleaning data

Collecting and importing data

Visualizing data

40. Which of the following is NOT a commonly used method for data pre-processing?

Data cleaning

Data integration

Data visualization

Data transformation

Page 5 of 8

41. When dealing with missing data in a dataset, what is a common approach for handling it?

Filling missing values with the mean of the column

Removing the entire row with missing data

Filling missing values with a random number

Ignoring the missing values

42. Which of the following is NOT a commonly used tool for data acquisition and pre-processing?

Python

SQL

Excel

Tableau

43. What is the process of combining data from multiple sources into a single, coherent view called?

Data visualization

Data integration

Data cleaning

Data transformation

44. Which of the following is an example of structured data in the context of data acquisition?

Images

Text files

CSV file

PDFs

45. Which of the following Python libraries is commonly used for data pre-processing tasks such as cleaning and transforming data?

NumPy

Matplotlib

TensorFlow

Pandas

46. What is the first step in the data acquisition process?

Data cleaning

Data validation

Data collection

Data visualization

47. What is the output of the following Python code snippet? ```python print(5 / 2) ```

2.5

2.0

2.2

48. In Python, what is the result of 2**3?

49. What statement is used to exit a loop prematurely in Python?

continue

return

break

pass

50. Which of the following Python libraries is commonly used for data manipulation and analysis?

Pandas

Matplotlib

NumPy

Scikit-learn

Page 6 of 8

51. What does the following Python code snippet do? ```python numbers = [1, 2, 3, 4, 5] squared = [x**2 for x in numbers] print(squared) ```

Prints the original list of numbers

Prints the square of each number in the list

Prints the sum of the numbers in the list

Prints the average of the numbers in the list

52. Which of the following is true about Python's function arguments?

Python supports named arguments but not default arguments

Python supports default arguments but not variable-length arguments

Python supports default arguments, named arguments, and variable-length arguments

Python does not support function arguments

53. What is the result of the following Python code? ```python a = 10 b = 5 result = a % b print(result) ```

54. What statistical analysis technique is used to determine the relationship between two continuous variables?

T-test

ANOVA

Pearson correlation

Chi-square test

55. Which statistical test is appropriate for comparing means between two independent groups?

Paired t-test

Wilcoxon signed-rank test

Independent samples t-test

ANOVA

56. What is the purpose of a confidence interval in statistical analysis?

To determine the significance level of a hypothesis test

To estimate the range within which the population parameter is likely to fall

To calculate the p-value of a statistical test

To identify outliers in a dataset

57. Which measure of central tendency is influenced by outliers in a dataset?

Mean

Median

Mode

Range

58. In statistical analysis, what does the term "p-value" represent?

The effect size of a study

The probability of wrongly rejecting a true null hypothesis

The confidence interval of a parameter estimate

The level of significance in a hypothesis test

59. Which statistical test is used to determine whether there is a significant difference between the means of two or more independent groups?

Chi-square test

Paired t-test

ANOVA

Wilcoxon signed-rank test

60. What does the coefficient of determination (R-squared) measure in statistical analysis?

The strength of the linear relationship between two variables

The probability of rejecting the null hypothesis

The variability in the dependent variable explained by the independent variable

The level of significance in a hypothesis test

Page 7 of 8

61. What statistical test is used to compare means between more than two groups or conditions?

Independent samples t-test

Paired t-test

ANOVA

Wilcoxon signed-rank test

62. What is the purpose of data analysis in the context of data modeling?

To clean and preprocess the data

To visualize the data

To identify patterns and relationships in the data

To deploy machine learning models

63. In the context of data modeling, what is overfitting?

Training a model on the training data until it perfectly fits the noise in the data

Training a model on the training data and achieving high accuracy

Training a model on the testing data and achieving high accuracy

A technique to handle missing values in the dataset

64. Which of the following is a common approach for data modeling?

Linear regression

K-means clustering

Principal component analysis (PCA)

Random forest

65. What is the goal of feature selection in data modeling?

To add more noise to the data

To reduce the complexity of the model

To overfit the model

To increase the accuracy of the model

66. Which technique is used to evaluate the performance of a data model?

Confusion matrix

Histogram

Scatter plot

Line chart

67. What is the purpose of cross-validation in data modeling?

To fit the model on the training data

To test the model on the training data to measure accuracy

To evaluate the model's performance on unseen data

To increase overfitting

68. What is the difference between regression and classification in data modeling?

Regression predicts continuous values, while classification predicts discrete categories

Regression predicts discrete categories, while classification predicts continuous values

Regression and classification are the same

Regression cannot be applied to categorical data

69. Which machine learning algorithm is commonly used for clustering in data modeling?

Decision tree

K-means

Linear regression

Random forest

70. Which of the following libraries in Python is commonly used for creating interactive visualizations?

NumPy

Pandas

Matplotlib

Scikit-learn

Page 8 of 8

71. What type of plot is best used for showing the relationship between two continuous variables?

Bar chart

Line plot

Scatter plot

Pie chart

PCED-30-01 Certified Entry-Level Data Analyst with Python Exam Free Dumps

PCED-30-01 Certified Entry-Level Data Analyst with Python Exam Free Dumps

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