Data Mining Practice Test

These questions are part of the practice quiz. Start practicing

• Data that does not have known outcome values for the attribute you wish to predict is called ________ data.
• Which description best fits a data mart?
• What is the formal name of a table column in database terminology?
• True or False: Business Understanding and Data Understanding are not necessary when you are confident that data is prepared and ready for analysis.
• True or False: A 25% support percent in an association set would be considered too low to be of any use.
• What is the statistical measure of how strong the relationships are between attributes in a data set?
• In RapidMiner, the data type binominal means:
• What is the name of the data set used to apply the predictive model in order to produce new predictions?
• Data types for independent variables in a decision tree model must be________.
• Which of the following best describes the CRISP-DM process?
• The discriminant analysis is a ______ model.
• In discriminant analysis, what is the name of the data set that is used for making predictions?
• In neural networks, what are the basic processing units that neurons are connected through?
• In the k-means algorithm, data points are assigned to the cluster with which of the following?
• What data type should the target attribute in linear regression be?
• Which data mining method is commonly used to uncover associations among items, such as rules like X implies Y?
• To prevent a k-Means model for a large data set from taking a long time to run, you can adjust the _________ parameter in RapidMiner.
• In the k-means clustering method, clusters are created around ________.
• According to the material, which method is recommended for handling missing data?
• The data type of the dependent variable in logistic regression must be binomial.
• Removing unwanted records from a data set can be accomplished by using a ________ operator in RapidMiner.
• When the values in one attribute tend to move in the same direction as the values in a correlated attribute, this is referred to as a __________ correlation.
• In the context of a predictive dataset in RapidMiner, which dataset is typically used to fit the model's parameters?
• In linear regression, what is the name of the attribute that will be predicted?
• When was the data mining process formalized by a group of companies?
• In logistic regression, the score values must lie within the lower and upper bounds defined by the training data.
• Decision trees are excellent predictive models when the dependent variable is _________.
• What is the general truth about correlation coefficients?
• What is the main purpose of the 'Apply Model' step in a predictive workflow?
• Selecting some subset of records from a data set is called ________ the data.
• In the linear regression method, what do the coefficients correspond to?
• In RapidMiner, data can be imported or read into the software from comma separated values, text, and spreadsheet files.
• In CRISP-DM, which phase focuses on understanding business objectives and constraints?
• Changing one categorical attribute into a series of binary attributes is known as ________.
• Taking observations or attributes out of a data set prior to data modeling is called _________, which is part of the Data Preparation step of CRISP-DM.
• In a decision tree, the root node represents the first predictive independent variable.
• Using two or three different modeling techniques on the same data and then comparing predicted outcomes across the different models is called ________.
• Which of the following is true about correlation?
• Which model type is used to assign items into predefined categories?
• Which of the following is NOT another name for a row of data in a database?
• In the k-Means clustering model, the table of average values for each attribute for all clusters is called a ______ table.
• True or false: Value ranges for all attributes for every observation in a scoring data set must be within the value ranges for the corresponding attributes in the training data set in a linear regression model.
• Correlation coefficients are generally considered strong if they are at least ______.
• In linear regression, all independent variables must be numeric.
• Which correlation value has the highest strength?
• Which of the following cannot be achieved using data mining software?
• Is it true that, like decision trees, neural networks can use any data type for independent attributes?
• Association Rules seeks to find frequent connections between _____________ in a data set.
• True or false: In the logistic regression model, the estimated regression coefficients are probabilities.
• In data mining workflows, which concept is used to designate the attribute that a predictive model should predict?
• OLAP stands for _________.
• True or False: FP-Growth creates association rules in RapidMiner.
• The logistic regression is a(n) ______ model.
• True or false: One can use binary values in the k-Means clustering model.
• In k-Means, what are the centers of clusters called?
• Which of the following is NOT another name for a column of data in a database?
• A _________ is a type of data store that is intentionally created for a specific business unit, usually for management and reporting purposes.
• In a logistic regression process, which Rapid Miner operator must be used to indicate the target attribute to be predicted?
• Logistic regression is typically used for predicting what type of outcome?
• In multiple linear regression, what statement best describes the intercept term?
• Which term describes the process of preparing data by removing inconsistencies and reducing redundancy?
• Which of the following should not be used to mark missing data in a data set?
• The attribute you want to predict in a predictive model is called a(n) _________.
• Which two major types of data mining models are identified?
• Using two or three different modeling techniques on the same data and then comparing predicted outcomes across the different models is called ________.
• True or false: Logistic regression is a predictive data mining model.
• The values in correlational analysis results are called ______.
• What is the name of the constant term in the simple linear regression equation?
• The formal name for a table column in database terminology?
• Which of the following names is not used for table rows in data mining terminology?
• Statistical correlations can be visualized using __________.
• Which algorithm is designed to efficiently uncover frequent itemsets and patterns in large data sets?
• Why might a data mining professional prefer a neural network over a decision tree model?
• _____________ is a tool that considers a number of variables and uses them for predicting the likelihood of either something happening or not happening.
• The algebraic expression of Linear Regression with multiple predictors can be derived from the n-NN model.
• What is the main goal of the evaluation step in the data mining process?
• Removing unwanted columns from a data set can be accomplished by using a ________ operator in RapidMiner.
• Which of the following is not an example of data scrubbing?
• Which statement about de-normalized data sets is correct?
• Which method is used to predict probabilities of outcomes rather than final class label?
• What is the typical use of a correlation matrix in recommender systems?
• Which values are derived from the training data in discriminant analysis to determine class membership?
• Line-by-line records of each item sold at a grocery store would be an example of ________.
• True or false: Linear regression is a categorical data mining model.
• The statement that the algebraic expression of Linear Regression with n independent variables can be derived from the n-NN model is false.
• The averages for each attribute in each cluster created by a k-Means model are called _______.
• Which statement about data scrubbing is true?
• A data store created for management and reporting for a single business unit is commonly called a
• In a decision tree model, you can leave an attribute in the data set even if it is neither a predictor attribute nor the target attribute as long as you define it as __________.
• Evaluation within CRISP-DM is intended to ensure that ______.
• Which operator is used to generate association rules in RapidMiner?
• Which of the following is NOT one of the six steps of CRISP-DM?
• A correlation matrix is a square table listing the correlation coefficients between pairs of attributes.
• Which correlation value has the lowest strength?
• Which statement describes the binominal data type in data mining?
• True or false: In a decision tree, some independent variables can be used more than once.
• Two standard deviations above the mean are also used to define outliers.
• The likelihood that the predicted category in a k-Nearest Neighbors or Naïve Bayes model is correct is known as the ______ percentage.
• Removing columns from a data set because they are not useful for a certain type of data analysis is an example of _________.
• Which assertion about independent variable data types in neural networks is correct?
• The k in k-Means indicates ________.
• The Naïve Bayes technique for predicting categorical outcomes employs both ________ and _______.
• In predictive modeling, the variable that is predicted is called the ______ variable.
• To create a valid logistic regression model, the data type for the attribute you wish to predict must be ______.
• A predictor in linear regression with a p-value near zero is considered to have a significant coefficient.
• A correlation coefficient is a single value that summarizes the strength and direction of a linear relationship.
• Which operator in RapidMiner is used to find frequent patterns in a dataset?
• Suppose that a human resources manager uses a linear regression model to predict income levels of their employees using two independent variables, Years of Education and Years of Experience. If the coefficient of Education is 2573, the coefficient of Experience is 373, and the intercept is 24975, what is the predicted income for a person with 16 years of education and 7 years of experience?
• The data type of the dependent variable in linear regression must be numeric.
• Data scrubbing allows us to handle anomalies that are present in the data set.
• Discriminant Analysis, k-Nearest Neighbors, and Naïve Bayes are analytic methods used to ______ events.
• If two attributes X and Y show a positive correlation, what does that imply for their relationship?
• In logistic regression, the smaller the p-value for an independent variable, the more predictive power that variable has relative to the dependent variable.
• What is the range for correlation coefficients between two variables?
• In CRISP-DM, if a problem is detected at the Modeling step, you should return to which step?
• In linear regression, the symbol x denotes the independent variable's value.
• Which of the following best describes the role of coefficients in linear regression?
• Which term describes the layer between the input layer and the output layer where learning occurs?
• In linear regression, the symbol b denotes the model's intercept.
• Which of the following is NOT a typical property of a binomial variable?
• Auditing an organization's databases, spreadsheets, file servers, and records repositories for information to use in data analysis is an example of ________.
• In logistic regression, what is the minimum confidence level recommended for dependable results?
• Under the CRISP-DM process for data analysis, if your evaluation of a model shows that the model is not useful, you should return to the ___________ step.
• True or false: Unlike some other predictive modeling techniques, decision tree models do not provide confidence percentages alongside their predictions.
• The dependent variable in logistic regression is binary.
• In linear regression scoring, to ensure scoring data attributes fall within the training data ranges, which RapidMiner operator is used to align the ranges?
• Data that are clearly inappropriate within a specific attribute in a data set are referred to as ________ data.
• In a decision tree, the first predictive independent variable is represented __________.
• A popular spreadsheet data file type name, CSV, stands for Comma Separated Values.
• In the linear regression method, designate an attribute to be predicted as 'label'. Which Rapid Miner operator can be used to do that?
• Across both linear and logistic regression, smaller p-values indicate greater predictive usefulness.
• Compared to decision trees, neural networks are typically better at modeling what?
• Which statement regarding data collection questions is true after data mining analysis?
• Which method is commonly used to handle missing values by substituting a statistic from the data?
• Which preprocessing concern is highlighted as important for improving k-means results?
• The numeric value that indicates the strength of the relationship between attributes in a data set is called the correlation ___________.
• Poor data organization leading to unreliable analysis is an example of which concept?
• In logistic regression, one designates an attribute to be predicted as 'label'. Which Rapid Miner operator can be used to do that?
• In order to create an association rules model, the data type for all attributes in the data set must be __________.
• Correlation is a statistical measure of how strong the relationships are between __________ in a data set.
• Reformatting phone numbers to a 12-character standard would take place in which phase?
• Missing values in a dataset mean that ______.
• Any value smaller (larger) than ______ standard deviations below (above) the mean is considered inconsistent?
• Which of the following is NOT a common name for one column in a data set that is arranged into a table?
• In the discriminant analysis method, what can be the data type of the attribute that is to be predicted?
• Any value that is smaller (or larger) than ______ standard deviations below (above) the mean is considered a statistical outlier.
• A data set is best described as which of the following?
• Which statement about FP-Growth in RapidMiner is true?
• True or false: The k-Means clustering is a non-predictive modeling technique.
• In FP-Growth, FP stands for what?
• In a decision tree, the term node refers to which of the following?
• Data arranged into columns and rows in a database are stored in which structure?
• OLAP systems are designed to support which type of data analysis?
• What term describes a single data value?
• A __________ is a subset of a database or data warehouse usually created for a specific analytic purpose.
• Modeling is the process of applying algorithms to data to seek out, identify, and display patterns.
• Which CRISP-DM phase involves cleaning data, removing incomplete records, and selecting relevant attributes?
• Which statement best describes the target of linear regression?
• Which parameter shortens runtime when clustering large datasets with k-Means in RapidMiner?
• The statement 'Minimum support percent should be 50 (0.5)' for association rules is:
• The data type required for all attributes in a data set in order to perform statistical correlation is _________.
• Which data mining model cannot predict a categorical target attribute?
• If the dependent variable is categorical, the neural network can be used for
• Because the mean is easily influenced by ______, it is important to handle such data before generating a k-Means model.
• True or false: When correlation coefficients reach the 'strong' or 'very strong' ranges, you have discovered statistical evidence that one attribute causes the other to change.
• Elimination of non-informative attributes to simplify a dataset is known as:
• If the dependent variable is numeric, the neural network is typically used for
• A good rule of thumb (though not a hard-and-fast rule) is that any value that is smaller than _____ standard deviations below the mean (or _____ standard deviations above the mean), is a statistical outlier.
• Data scrubbing primarily aims to improve data quality by:
• Which outcome is typically produced by logistic regression?
• During which phase is data auditing and inventory of data sources typically performed?
• The dataset used to apply a predictive model to generate new predictions is called the ______ data.
• Which statement is true according to the material?
• Which values can be used for a binominal variable?
• True or False: Data mining modeling techniques can classify, predict, or both.
• Which statement best describes data type requirements for independent variables in a decision tree?
• Scatterplots are a method of visualizing statistical correlations.
• Databases designed to support a high number of reads and writes are referred to as ________.
• How many data sets are required to implement linear regression?
• What is the first step in the CRISP-DM process?
• What data type must a data set's attributes be in order to implement association rules in RapidMiner?
• True or false: Decision trees are better than more numerical approaches (such as linear regression) at handling attributes that have missing or inconsistent values.
• In RapidMiner, operators are connected to each other through ____________.
• Which phase directly follows Data Understanding in the CRISP-DM sequence?
• Which term describes the rule-based structure used to express associations between items?
• What type of correlation occurs when two attributes are correlated to one another, and as the values in one attribute increase, the values in the other attribute decrease?
• In CRISP-DM, the data preparation step includes reducing the dataset by removing irrelevant attributes or records.
• True or false: k-Means is a non-predictive, unsupervised learning method.
• Which statement correctly describes the typical nature of the dependent variable in logistic regression?
• Establishing permission to use company data in analytic activities should take place during which CRISP-DM phase?
• A value of 'middle-aged' in an attribute that otherwise contains peoples' ages in number of years would be an example of _______.
• OLTP systems are primarily used for which of the following?
• What does the acronym GIGO stand for in data processing?
• In RapidMiner, the attribute you wish to predict must be set to the role of ________.
• What is the standard language used to manage and access data stored in relational databases?
• If a value is exactly two standard deviations below the mean, how is it classified according to the rule about inconsistencies?
• In linear regression, which Rapid Miner operator is used to connect training data set stream with scoring data set stream?
• A business analytics professional wants to predict the likelihood of patients to have a second heart attack using their past data. Which of the following models should s/he use?
• In an association rule, which metric measures the probability of the consequent given the antecedent?
• Which of the following data mining models uses both classification and prediction techniques?
• Consider the paired values of two attributes, X and Y, shown below. This is an example of:
• What action should be taken when a decision tree has too many nodes or leaves? (alternative wording)
• True or false: One must make sure that there are no outlier values in the data set before running the k-Means clustering model.
• What term describes converting a categorical feature into binary indicators for each category?
• Which of the following statements about cluster numbering in k-Means is true?
• To view which observations are assigned to each cluster in a k-Means model in RapidMiner, which feature should you use?
• In a linear model, which quantity represents the change in the predicted outcome per unit increase in a predictor, holding others constant?
• True or false: In order to use a neural network model, one must make sure that the ranges for the scoring data sets are within the ranges for the training data.
• True or False: It is not permissible at any point in the CRISP-DM process to return to an earlier step.
• To remove unwanted observations from a data set in RapidMiner, use the _______ operator.
• What process involves comparing the outputs of multiple modeling techniques to reach a conclusion?
• In discriminant analysis, which values are calculated from the training data?
• Discriminant analysis, k-Nearest Neighbors, and Naïve Bayes are all analytic methods used to __________.
• What type of correlation occurs when two attributes are correlated to one another, and as the values in one attribute decrease, the values in the other attribute also decrease?
• True or false: The neural network is both a predictive data mining model and a classification model.
• What is the mathematical formula for the simple linear regression?
• Normalization primarily aims to reduce redundancy by organizing data into related entities. True or False?
• Which statement best describes simple linear regression?
• Which of the following values can be used for a binomial variable?
• Which layer in a neural network produces the final predictions?
• What is the mathematical formula for multiple linear regression?
• Standard deviation measures how dispersed the values are around the __________________.
• Which of the following is not a correlation coefficient type?
• True or false: Logistic regression is a categorical data mining model.
• True or false: In the logistic regression model, the scoring values must all fall within the lower and upper bounds set by the corresponding values in the training data set.
• What is the name of the operation used to retrieve data from a database?
• In a neural network, the dependent variable can be which data types?
• In the Association Rules model, the minimum confidence percent should be 90 (or 0.9).
• Which company is not among those that developed the data mining process used in class?
• True or False: The FP-Growth function is required in RapidMiner to create association rules.
• Which data type is explicitly required for independent variables in neural network modeling?
• Which of the following is not considered a data format?
• A binominal variable can take exactly two values.
• The Association Rules model seeks to find frequent connections between observations in a data set.
• To predict the probability of a binary outcome, which model is most appropriate?
• For association rules modeling, the data type of all attributes is typically __________.
• Which data mining method does Amazon.com use to recommend additional products when you search or buy something on its website?
• _______ is a process of combining multiple tables into a single table in spite of the fact that this may introduce duplicate data in some columns.
• In RapidMiner, what is the required role designation for the variable the model predicts?
• Removing records that contain missing or inconsistent data from a dataset before analysis is an example of ________.
• True or false: Unlike in linear regression, it is possible to have more than one dependent variable in a logistic regression model.
• In data analysis, the output of correlation analysis is typically represented as a ...
• Which statement best describes the typical effect of denormalization on data redundancy?
• Which term names the constant portion of the regression equation?
• To remove unwanted attributes from a data set in RapidMiner, use the _______ operator.
• What term describes data containing known outcome values for the attribute you wish to predict?
• Which statement best describes correlation coefficients?
• Which dataset is typically used to fit the parameters of a predictive model?
• K-Means clustering is described as what kind of model?
• Given a correlation value of 0.762 between Number of Monthly Credit Card Purchases and Debt-to-Income Ratio, what pattern would you expect?
• Non-ordered nominal attributes can be recoded using which coding scheme?
• Scatterplots can show correlations among more than two attributes at once.
• The required data type for all attributes in an association rule model in RapidMiner is _______.
• In relational databases and data analytics software programs such as RapidMiner, each attribute is assigned a __________, which restricts the kind of data that can be stored in the attribute.
• Standard deviation measures how dispersed the values are around the mean.
• Which statement best describes discriminant analysis?
• Which term is NOT commonly used to refer to a single row in a data table?
• Which of the following options refers to the operation used to designate an attribute's role in a data-mining tool to decide its use in models?
• A Data Set is usually a which type of table derived from a relational database or data warehouse?
• CSV files are a popular format for tabular data.
• Data analysis processes in RapidMiner are built using rectangular building blocks called ________.
• Databases designed to support a dimensional examination and aggregation are referred to as ________.
• Under the CRISP-DM process for data analysis, ________ is the process of applying algorithms to data to seek out, identify, and display patterns or messages found in the data.
• In linear regression, the symbol m denotes the independent variable's coefficient.
• In a relational database, a vertical partition of data within a table is called a
• Two standard deviations below the mean is used to define an outlier.
• The mean, median, and mode are collectively known as
• Denormalization is sometimes used to optimize query performance at the expense of data redundancy.
• Which statement about data marts and data warehouses is accurate?
• In data mining, association rules are commonly used to generate which type of outputs?
• The process of breaking data tables apart into related entities in order to reduce redundancy in the data is called _________.
• Removing incomplete or inaccurate records and removing columns that are not interesting are activities that would most likely take place in the __________ step of the CRISP-DM model.
• In a decision tree, the independent variable found at each branch of the tree is known as a _________.
• True or false: The neural network is a classification model.
• Which of the following is a direct effect of normalization?
• True or False: A confidence percent of 25% in an association set would be considered too low to be of any use.
• Conducting data mining and analytics on high-volume transactional database systems is recommended because such systems have the most up-to-date data.
• Which of the following operators must be used if an attribute needs to be visible in the data set but ignored by Rapid Miner models.
• Using certain data mining tools, one can predict future outcomes.
• In linear regression, the p-value for an independent variable is used to judge the significance of the variable.
• True or false: The cluster number assigned to each cluster in RapidMiner indicates the relative importance of each cluster when compared to the others.
• If two attributes have a strong positive correlation, increasing one will likely increase the other.
• The space between independent variables and the dependent variable where the model gets trained is called the hidden layer.
• The data types of all independent variables in linear regression must be numeric.
• In order to describe data, we often use arithmetic functions such as the mean, median, and mode. These three functions are known as _________.
• Which RapidMiner operator can be used to display the attribute values that belong to a particular cluster?
• To conduct correlational analysis in data mining software, we use the Correlation Matrix.
• True or false: In a decision tree, a variable can appear on multiple branches.
• What is the best method we have learned so far to handle missing data in a data set?
• An attribute used to predict outcome values in a predictive model is called a(n) _________.
• Which of the following is not among the data preparation activities?
• In a linear regression model, any predictor attribute with a p-value close to 1 is not ______.
• Which coding method is described for transforming nominal attributes like eye color into numeric features in some models?
• What is the correlation coefficient when there is a perfect correlation between two variables?
• A popular database language, SQL, stands for Standard Query Language.
• Amazon.com implements the 'Correlation Matrix' in order to recommend items to visitors on their website.
• Which of the following statements is true about using binary values in k-Means?
• Which data analytics software example is mentioned as assigning data types to attributes?
• The k-Means clustering technique for data analysis is ideal for _________.
• In model evaluation, describing the practice of using two or more models and comparing their results on the same data is called what?
• If a data analyst finds that a decision tree model has too many nodes or leaves to be meaningful, the analyst should apply _________ to the tree.
• True or false: The neural network is a predictive data mining model.
• Is it permissible to loop back to earlier steps in CRISP-DM?
• In the logistic regression workflow, which Rapid Miner operator connects the training data stream with the scoring data stream?
• Which phase is primarily concerned with ensuring that the data supports reliable and useful conclusions?
• Considerations for Data Understanding include all of the following EXCEPT _________.
• In RapidMiner, the attribute to be predicted must have its role set to which term?
• In RapidMiner, you can leave an attribute in a predictive model's data set even if it is neither a predictor attribute nor the target attribute as long as you set the role to ______.
• The data types of all independent variables in logistic regression must be numeric.
• In RapidMiner, each rectangle in a data mining process view is called what?
• Which of the following questions cannot be answered after analyzing data using data mining software?
• What does the letter 'k' in k-means clustering stand for?
• In RapidMiner, which operator keeps only the desired attributes?
• In CRISP-DM, which step focuses on confirming the business objective and constraints before modeling?
• Data quality: Which data term describes non-sensical values in an attribute like a street name in a gender field?
• The linear regression is a(n) ______ model.
• True or false: The values true/false or 0/1 would both be valid combinations for the dependent variable in a logistic regression model.
• What is the algebraic formula used to create predictions in a linear regression model?
• In k-Means, the parameter k represents the number of clusters. This is called what?
• In the logistic regression workflow, the ranges for all attributes in the scoring data must be within the ranges for the training data. Which operator can be used to match these ranges?
• Which statement best describes Folder view in RapidMiner?
• In data mining, missing value means zero.
• In neural networks, the pathways between independent variables and dependent variables are called
• Which of the following is not a spreadsheet data file type?