INTRO TO DATA ANALYTICS EXAM
STUDY GUIDE QUESTIONS AND
ANSWERS
Time series analysis - ANSWER-A forecasting method that uses historical sales data
to discover patterns in the firm's sales over time and generally involves trend, cycle,
seasonal, and random factor analyses
Factor analysis - ANSWER-correlations among many variables are analyzed to
identify closely related clusters of variables
Association rules analysis - ANSWER-specify a relation between attributes that
appears more frequently than expected if the attributes were independent.
Text analysis - ANSWER-A process for extracting value from large quantities of
unstructured text data.
Principal component analysis - ANSWER-a statistical method to simplify the
description of a set of interrelated variables. Its general objectives are data reduction
and interpretation; there is no separation into dependent and independent variables;
the original set of correlated variables is transformed into a smaller set of
uncorrelated variables called the principal components. Often used as the first step
in a factor analysis.
Multiple regression - ANSWER-a statistical technique that computes the relationship
between a predictor variable and a criterion variable, controlling for other predictor
variables
Logistic regression - ANSWER-A statistical analysis which determines an individual's
risk of the outcome as a function of a risk factor. The outcome of interest has two
categories.
standard deviation - ANSWER-a computed measure of how much scores vary
around the mean score
coefficient of determination - ANSWER-a measure of the amount of variation in the
dependent variable about its mean that is explained by the regression equation
p-value - ANSWER-The probability level which forms basis for deciding if results are
statistically significant (not due to chance).
The probability of observing a test statistic as extreme as, or more extreme than, the
statistic obtained from a sample, under the assumption that the null hypothesis is
true.
Linear regression - ANSWER-a statistical method used to fit a linear model to a
given data set
, Nonlinear regression - ANSWER-Used if a hypothesis exists that suggests a
curvilinear relationship between the predictor variables and the criterion variable.
Random forest - ANSWER-An algorithm used for regression or classification that
uses a collection of tree data structures trees "vote" on the best model
Naive Bayes - ANSWER-Classification predictive
Training data classify new data points
ie red, round, Apple, yellow, oblong,banana
If new obj red then more likely Apple
SPSS modeler - ANSWER-It is used for applying the trained model to new data for
predictions
model execution phase
Feature selection - ANSWER-the process of selecting attributes which are most
predictive of the class we are predicting
Cross-validation - ANSWER-Verifying the results obtained from a validation study by
administering a test or test battery to a different sample (drawn from the same
population)
Data preprocessing - ANSWER-A tedious process of converting raw data into an
analytic ready state.
Model Deployment - ANSWER-the process of putting machine learning models into
production
Result analysis - ANSWER-detailed description of the results obtained through
experimentation.
Data post-processing - ANSWER-simple way of applying mathematical expressions,
logic arithmetic and conditional functions to data
Operationalization - ANSWER-the process of assigning a precise method for
measuring a term being examined for use in a particular study
Ruby - ANSWER-Has a dynamic type system and automatic memory management.
Swift - ANSWER-powerful and intuitive programming language optimized when
running on iOS, macOS, and other Apple platforms
MATLAB - ANSWER-used for a variety of mathematical calculations and tasks
Data scientist - ANSWER-extracts knowledge from data by performing statistical
analysis, data mining, and advanced analytics on big data to identify trends, market
changes, and other relevant information
STUDY GUIDE QUESTIONS AND
ANSWERS
Time series analysis - ANSWER-A forecasting method that uses historical sales data
to discover patterns in the firm's sales over time and generally involves trend, cycle,
seasonal, and random factor analyses
Factor analysis - ANSWER-correlations among many variables are analyzed to
identify closely related clusters of variables
Association rules analysis - ANSWER-specify a relation between attributes that
appears more frequently than expected if the attributes were independent.
Text analysis - ANSWER-A process for extracting value from large quantities of
unstructured text data.
Principal component analysis - ANSWER-a statistical method to simplify the
description of a set of interrelated variables. Its general objectives are data reduction
and interpretation; there is no separation into dependent and independent variables;
the original set of correlated variables is transformed into a smaller set of
uncorrelated variables called the principal components. Often used as the first step
in a factor analysis.
Multiple regression - ANSWER-a statistical technique that computes the relationship
between a predictor variable and a criterion variable, controlling for other predictor
variables
Logistic regression - ANSWER-A statistical analysis which determines an individual's
risk of the outcome as a function of a risk factor. The outcome of interest has two
categories.
standard deviation - ANSWER-a computed measure of how much scores vary
around the mean score
coefficient of determination - ANSWER-a measure of the amount of variation in the
dependent variable about its mean that is explained by the regression equation
p-value - ANSWER-The probability level which forms basis for deciding if results are
statistically significant (not due to chance).
The probability of observing a test statistic as extreme as, or more extreme than, the
statistic obtained from a sample, under the assumption that the null hypothesis is
true.
Linear regression - ANSWER-a statistical method used to fit a linear model to a
given data set
, Nonlinear regression - ANSWER-Used if a hypothesis exists that suggests a
curvilinear relationship between the predictor variables and the criterion variable.
Random forest - ANSWER-An algorithm used for regression or classification that
uses a collection of tree data structures trees "vote" on the best model
Naive Bayes - ANSWER-Classification predictive
Training data classify new data points
ie red, round, Apple, yellow, oblong,banana
If new obj red then more likely Apple
SPSS modeler - ANSWER-It is used for applying the trained model to new data for
predictions
model execution phase
Feature selection - ANSWER-the process of selecting attributes which are most
predictive of the class we are predicting
Cross-validation - ANSWER-Verifying the results obtained from a validation study by
administering a test or test battery to a different sample (drawn from the same
population)
Data preprocessing - ANSWER-A tedious process of converting raw data into an
analytic ready state.
Model Deployment - ANSWER-the process of putting machine learning models into
production
Result analysis - ANSWER-detailed description of the results obtained through
experimentation.
Data post-processing - ANSWER-simple way of applying mathematical expressions,
logic arithmetic and conditional functions to data
Operationalization - ANSWER-the process of assigning a precise method for
measuring a term being examined for use in a particular study
Ruby - ANSWER-Has a dynamic type system and automatic memory management.
Swift - ANSWER-powerful and intuitive programming language optimized when
running on iOS, macOS, and other Apple platforms
MATLAB - ANSWER-used for a variety of mathematical calculations and tasks
Data scientist - ANSWER-extracts knowledge from data by performing statistical
analysis, data mining, and advanced analytics on big data to identify trends, market
changes, and other relevant information
