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PYTHON INSTITUTE PCED-30-01 28% OFF Automatically For You Certified Entry-Level Data Analyst with Python
1.In the context of data acquisition, what does ETL stand for? A. Extract, Transform, Load B. Extract, Transfer, Load C. Edit, Transform, Load D. Enhance, Transform, Load Answer: A
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2.Which of the following is NOT a commonly used data acquisition method? A. Web scraping B. API integration C. Data visualization D. Manual data entry Answer: C
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3.What is the purpose of data pre-processing in a data analytics workflow? A. To make the data more difficult to analyze B. To remove noise and irrelevant information C. To increase the computational complexity D. To slow down the data analysis process Answer: B
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4.Which of the following techniques can be used in data pre-processing to handle missing values? A. Removing rows with missing values B. Replacing missing values with the mean of the column C. Ignoring missing values altogether D. Filling missing values with zeros Answer: B
5.What is outlier detection in the context of data pre-processing? A. Identifying extreme values or anomalies in the data B. Highlighting positive trends in the data C. Analyzing data to predict future outcomes D. Sorting data based on a predefined criteria Answer: A
6.Which of the following is NOT an example of data cleaning in the pre-processing stage?
A. Removing duplicate entries B. Converting categorical data to numerical values C. Handling missing values D. Aggregating data from multiple sources without validation Answer: D
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7.Why is data normalization important in data pre-processing? A. It helps in increasing the size of the dataset B. It ensures that all features have the same scale C. It makes the data difficult to interpret D. It slows down the data analysis process Answer: B
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8.Which of the following techniques can be used in data pre-processing for feature selection? A. Principal Component Analysis (PCA) B. Support Vector Machines (SVM) C. k-Nearest Neighbors (k-NN) D. Linear Regression Answer: A
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9.What does the "len()" function in Python do? A. Returns the sum of all elements in a list B. Returns the average of elements in a list C. Returns the number of elements in a list D. Returns the maximum value in a list Answer: C
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10.What is the correct way to comment a single line of code in Python? A. // This is a comment B. /* This is a comment */ C. # This is a comment D. Answer: C
11.Which of the following is used to perform integer division in Python? A. / B. //
C. * D. % Answer: B
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13.Which of the following is not a valid variable name in Python? A. my_var B. myVar C. 1_var D. _var Answer: C
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12.What is the output of the following code snippet? ```python x = 5 y = 2 print(x ** y) ``` A. 7 B. 10 C. 25 D. 32 Answer: C
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14.What does the "range()" function in Python do? A. Generates a list of numbers B. Filters elements in a list C. Returns the length of a list D. Reverses the order of elements in a list Answer: A
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15.What is the main purpose of statistical analysis in data analytics? A. To organize data B. To visualize data C. To draw conclusions from data D. To collect data Answer: C
16.Which measure of central tendency is affected by outliers? A. Mean B. Median C. Mode D. Range
Answer: A
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18.What does skewness measure in a data distribution? A. Spread of the data B. Symmetry of the data C. Deviation from the mean D. Kurtosis of the data Answer: B
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17.When is the mode the most appropriate measure of central tendency to use? A. When the data is normally distributed B. When the data has outliers C. When the data is skewed D. When the data is categorical Answer: D
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19.Which statistical test is used to determine if there is a significant difference between the means of two independent groups? A. T-test B. ANOVA C. Chi-square test D. Regression analysis Answer: A
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20.What is the p-value in hypothesis testing? A. The probability of making a Type I error B. The probability of making a Type II error C. The level of significance D. The probability of observing the test statistic Answer: D
21.Which type of correlation coefficient indicates a strong positive linear relationship between two variables? A. -1.0 B. 1.0 C. 0.5 D. 0.0 Answer: B
22.What is the purpose of regression analysis in statistical analysis? A. To summarize the data B. To determine cause and effect relationships C. To identify trends over time D. To calculate probabilities Answer: B
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23.What is the purpose of data analysis in the context of a Python programming for data analytics? A. To collect data B. To visualize data C. To interpret data D. To delete data Answer: C
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24.Which of the following Python libraries is commonly used for data analysis and modeling? A. TensorFlow B. Matplotlib C. NumPy D. Django Answer: C
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25.What is the goal of data modeling in the field of data analytics? A. To organize data B. To analyze data C. To make predictions based on data D. To clean data Answer: C
26.In data analytics, what does the term "feature engineering" refer to? A. Creating new features from existing data B. Removing features from the dataset C. Engineering the physical features of the data D. Analyzing features in detail Answer: A
27.Which technique is commonly used in machine learning for splitting a dataset into training and testing sets? A. Randomization B. Normalization C. One-hot encoding D. Train-test split Answer: D
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28.What is the process of evaluating a model's performance using data that the model has not seen during training known as? A. Model validation B. Model training C. Model testing D. Model optimization Answer: C
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29.Which of the following metrics is commonly used to evaluate classification models in data analytics? A. Mean Squared Error B. Receiver Operating Characteristic (ROC) curve C. R-squared D. Accuracy Answer: D
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30.What is the process of fine-tuning a machine learning model to improve its performance known as? A. Model validation B. Hyperparameter tuning C. Data preprocessing D. Feature selection Answer: B
31.Which of the following libraries in Python is commonly used for data visualization? A. numpy B. pandas C. matplotlib D. scikit-learn Answer: C
32.What type of plot would be most suitable for showing the distribution of a single numerical variable? A. Scatter plot B. Bar plot C. Histogram D. Box plot Answer: C
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33.Which function in pandas is used to create a line plot from a DataFrame? A. plot() B. scatter() C. boxplot() D. hist() Answer: A
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34.In a line plot, what do the points connected by a line represent? A. Mean values B. Median values C. Maximum values D. Sequential data points Answer: D
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35.Which of the following is an advantage of using seaborn for data visualization in Python? A. Limited customization options B. High-level interface for creating attractive plots C. Slow rendering speed D. Limited compatibility with other libraries Answer: B
36.What type of plot would be most suitable for comparing the distribution of a numerical variable across different categories? A. Scatter plot B. Pie chart C. Box plot D. Bar plot Answer: D
37.Which of the following is an advantage of using interactive plots for data visualization? A. Limited user engagement B. Ability to zoom, pan, and interact with data C. Fixed visual display D. Slow rendering speed Answer: B
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38.What type of plot is commonly used to visualize the relationship between two numerical variables? A. Box plot B. Scatter plot C. Histogram D. Pie chart Answer: B
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39.What is the purpose of data acquisition in data analytics? A. Storing data B. Cleaning data C. Collecting and importing data D. Visualizing data Answer: C
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40.Which of the following is NOT a commonly used method for data pre-processing? A. Data cleaning B. Data integration C. Data visualization D. Data transformation Answer: C
41.When dealing with missing data in a dataset, what is a common approach for handling it? A. Filling missing values with the mean of the column B. Removing the entire row with missing data C. Filling missing values with a random number D. Ignoring the missing values Answer: A
42.Which of the following is NOT a commonly used tool for data acquisition and preprocessing? A. Python B. SQL C. Excel D. Tableau Answer: D
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43.What is the process of combining data from multiple sources into a single, coherent view called? A. Data visualization B. Data integration C. Data cleaning D. Data transformation Answer: B
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44.Which of the following is an example of structured data in the context of data acquisition? A. Images B. Text files C. CSV file D. PDFs Answer: C
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45.Which of the following Python libraries is commonly used for data pre-processing tasks such as cleaning and transforming data? A. NumPy B. Matplotlib C. TensorFlow D. Pandas Answer: D
46.What is the first step in the data acquisition process? A. Data cleaning B. Data validation C. Data collection D. Data visualization
Answer: C
47.What is the output of the following Python code snippet? ```python print(5 / 2) ``` A. 2.5 B. 2 C. 2.0 D. 2.2 Answer: A
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48.In Python, what is the result of 2**3? A. 6 B. 5 C. 8 D. 4 Answer: C
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49.What statement is used to exit a loop prematurely in Python? A. continue B. return C. break D. pass Answer: C
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50.Which of the following Python libraries is commonly used for data manipulation and analysis? A. Pandas B. Matplotlib C. NumPy D. Scikit-learn Answer: A
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) ``` A. Prints the original list of numbers B. Prints the square of each number in the list C. Prints the sum of the numbers in the list D. Prints the average of the numbers in the list Answer: B
52.Which of the following is true about Python's function arguments? A. Python supports named arguments but not default arguments B. Python supports default arguments but not variable-length arguments C. Python supports default arguments, named arguments, and variable-length arguments D. Python does not support function arguments Answer: C
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53.What is the result of the following Python code? ```python a = 10 b = 5 result = a % b print(result) ``` A. 2 B. 5 C. 0 D. 1 Answer: D
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54.What statistical analysis technique is used to determine the relationship between two continuous variables? A. T-test B. ANOVA C. Pearson correlation D. Chi-square test Answer: C
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55.Which statistical test is appropriate for comparing means between two independent groups? A. Paired t-test B. Wilcoxon signed-rank test C. Independent samples t-test D. ANOVA Answer: C
56.What is the purpose of a confidence interval in statistical analysis? A. To determine the significance level of a hypothesis test B. To estimate the range within which the population parameter is likely to fall C. To calculate the p-value of a statistical test D. To identify outliers in a dataset
Answer: B
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58.In statistical analysis, what does the term "p-value" represent? A. The effect size of a study B. The probability of wrongly rejecting a true null hypothesis C. The confidence interval of a parameter estimate D. The level of significance in a hypothesis test Answer: B
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57.Which measure of central tendency is influenced by outliers in a dataset? A. Mean B. Median C. Mode D. Range Answer: A
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59.Which statistical test is used to determine whether there is a significant difference between the means of two or more independent groups? A. Chi-square test B. Paired t-test C. ANOVA D. Wilcoxon signed-rank test Answer: C
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60.What does the coefficient of determination (R-squared) measure in statistical analysis? A. The strength of the linear relationship between two variables B. The probability of rejecting the null hypothesis C. The variability in the dependent variable explained by the independent variable D. The level of significance in a hypothesis test Answer: C
61.What statistical test is used to compare means between more than two groups or conditions? A. Independent samples t-test B. Paired t-test C. ANOVA D. Wilcoxon signed-rank test
Answer: C
62.What is the purpose of data analysis in the context of data modeling? A. To clean and preprocess the data B. To visualize the data C. To identify patterns and relationships in the data D. To deploy machine learning models Answer: C
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63.In the context of data modeling, what is overfitting? A. Training a model on the training data until it perfectly fits the noise in the data B. Training a model on the training data and achieving high accuracy C. Training a model on the testing data and achieving high accuracy D. A technique to handle missing values in the dataset Answer: A
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64.Which of the following is a common approach for data modeling? A. Linear regression B. K-means clustering C. Principal component analysis (PCA) D. Random forest Answer: D
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65.What is the goal of feature selection in data modeling? A. To add more noise to the data B. To reduce the complexity of the model C. To overfit the model D. To increase the accuracy of the model Answer: B
66.Which technique is used to evaluate the performance of a data model? A. Confusion matrix B. Histogram C. Scatter plot D. Line chart Answer: A
67.What is the purpose of cross-validation in data modeling? A. To fit the model on the training data B. To test the model on the training data to measure accuracy C. To evaluate the model's performance on unseen data D. To increase overfitting Answer: C
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68.What is the difference between regression and classification in data modeling? A. Regression predicts continuous values, while classification predicts discrete categories B. Regression predicts discrete categories, while classification predicts continuous values C. Regression and classification are the same D. Regression cannot be applied to categorical data Answer: A
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69.Which machine learning algorithm is commonly used for clustering in data modeling? A. Decision tree B. K-means C. Linear regression D. Random forest Answer: B
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70.Which of the following libraries in Python is commonly used for creating interactive visualizations? A. NumPy B. Pandas C. Matplotlib D. Scikit-learn Answer: C
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