Data Analytics Flashcards
Fishbone diagrams are most often used in
A. Prescriptive analysis.
B. Descriptive analysis.
C. Diagnostic analysis.
D. Predictive analysis.
C. Diagnostic analysis.
A fishbone diagram is a total quality management process improvement method that is useful in studying causation (why the actual and desired situations differ). It is often used in diagnostic analysis, which provides insights into the reason certain results occur.
The 4 V’s of Big Data
Volume
Variety
Velocity
Veracity
Under what data analytics method would dashboards and score cards be used?
A. Descriptive.
B. Prescriptive.
C. Diagnostic.
D. Predictive.
C. Diagnostic.
Dashboards and score cards break down an observation into different aspects to facilitate the identification of the reason certain results occur.
Under which category of data analysis should “anomaly detection” be classified?
A. Diagnostic analysis.
B. Descriptive analysis.
C. Prescriptive analysis.
D. Predictive analysis.
B. Descriptive analysis.
The purpose of anomaly detection is to identify unusual patterns or deviations from the norm or expected results. The focus of anomaly detection is on the reporting of historical information (i.e., descriptive analysis).
The new purchasing director is analyzing purchase orders for the organization. Which of the following analyses would best be displayed on a histogram?
A. The organization purchased US $27 million worth of inventory in the past year. Distribute by value, using US $500 increments, the quantity of purchase orders that fall within each range.
B. In the past year the organization placed 10,000 purchase orders. Organize the number of orders placed with each supplier, sorted in descending order.
C. Identify and organize the reasons the average turnaround time for purchase orders falls outside the control parameters of 4-10 days.
D. The average turnaround time from issuing a purchase order to receiving the merchandise is 7 days. Review the last 2,000 purchase orders, and using 10 days as the upper control limit and 4 days as the lower control limit, graph the turnaround time for each order.
A. The organization purchased US $27 million worth of inventory in the past year. Distribute by value, using US $500 increments, the quantity of purchase orders that fall within each range.
The histogram displays a continuous frequency distribution of the independent variable in the form of a bar graph. The y axis is the quantity of purchase orders and the x axis is the purchase order amount. The histogram would best display the quantity of purchase orders by dollar value.
Which of the following statements is correct if there is an increase in the resources available within an economy?
A. The standard of living in the economy will rise.
B. The technological efficiency of the economy will improve.
C. More goods and services will be produced in the economy.
D. The economy will be capable of producing more goods and services.
D. The economy will be capable of producing more goods and services.
If demand is sufficient and society can employ the resources, more goods and services will be produced.
The type of data analytics that is most likely to yield the most impact for an organization but is also the most complex is called
A. Prescriptive analysis.
B. Diagnostic analysis.
C. Predictive analysis.
D. Descriptive analysis.
A. Prescriptive analysis.
Prescriptive analysis uses descriptive, diagnostic, and predictive analytics to improve business strategy. It concentrates on what an organization needs to do in order for the predicted future results to actually occur. This type of analytics provides the most benefit but requires the most inputs.
A hospital has observed an increase in the number of cases of a disease and has asked an analyst to collect data on the cases over the last 3 years. The analyst noted that the disease appeared 3 years ago during the second quarter of the year. Since then, the third and fourth quarters of each year showed significant spikes in the number of cases when compared to the first two quarters. What is the best way to present these findings?
A. Bar graph, showing the number of cases in each quarter for the last 3 years.
B. Scatter plot, showing the change in the number of cases for each quarter for the last 3 years.
C. Table, showing the number of cases in each month for the last 3 years.
D. Pie chart, showing the number of cases in each quarter for the last 3 years.
A. Bar graph, showing the number of cases in each quarter for the last 3 years.
A bar chart (also called bar graph) is the best way to present the findings because it shows the number of cases each quarter in comparison to other quarters.
Each of the following represents a characteristic of big data except
A. Mixture.
B. Speed.
C. Size.
D. Uniformity.
D. Uniformity.
Big data is often characterized by the “4 Vs” - volume, variety, velocity, and veracity. Thus, uniformity is not a characteristic of big data.
Data fusion is best described as the
A. Examination of data to discover unexpected patterns.
B. Assurance of data quality.
C. Process of integrating data and knowledge.
D. Prediction of outcomes and behaviors.
C. Process of integrating data and knowledge.
Data fusion is the process of integrating data and knowledge representing the same real-world object into a more consistent, accurate, and useful representation than the individual sources.
Which of the following visualization methods is most suitable for retaining data details?
A. Histogram.
B. Table.
C. Dot maps.
D. Line chart.
B. Table.
Tables present data in as close to their raw form as possible and are able to retain the details of the data.
Bubble charts, while similar to scatter plots, add a third variable, which is
A. Rectangles of different colors and sizes.
B. Colors and shading.
C. Time-series data.
D. The size of data points.
D. The size of data points.
Bubble charts have two quantitative variables plotted on the x- and y-axes to depict the relationship between the variables. Bubble charts add a third variable to scatter plots by utilizing the sizes of the data points.
Which of the following are key technologies of big data?
I. In-memory analytics
II. Data mining
III. Text mining
A. II only.
B. I, II, and III.
C. I only.
D. I and III only.
B. I, II, and III.
Key technologies of big data include data mining, text mining, data management, in-memory analytics, predictive analytics, and Hadoop.
Which of the following is a true statement regarding data visualization?
A. Data visualization is the use of computers to convey information.
B. Data visualization tends to convey more complete information than raw data.
C. Data visualization is always the most appropriate way for presenting data.
D. Data visualization can take various forms.
D. Data visualization can take various forms.
Data visualization may take various forms depending on the purposes and needs of a given situation. Examples of data visualization includes tables, graphs, charts, maps, and images.
Flushing out useless information is a step in
A. Data cleaning.
B. Data normalization.
C. Data discovery.
D. Data mining.
A. Data cleaning.
Data cleaning consists of flushing out useless information and identifying missing data.
Which product line contributed the greatest percentage of revenue in 2019?
A. Sporting goods.
B. Home goods.
C. Clothing.
D. Jewelry.
C. Clothing.
In 2019, clothing contributed the greatest percentage of revenue, as depicted by the largest area in the center of the chart.
Which product line has shown continuous growth in revenue from 2018 to 2020?
A. Electronics.
B. Home goods.
C. Sporting goods.
D. Clothing.
C. Sporting goods.
The continuous growth of sporting goods is depicted by the expanding percentage of revenue from 2018 to 2020.
Data Visualization:
Tables
Data Visualization:
Bar Graphs
Data Visualization:
Bar Graphs with Time-Series Data
Data Visualization:
Bar Graphs with Colors or Patterns
Data Visualization:
Bar Graphs with Varying Bar Widths
Data Visualization:
Histograms
Data Visualization:
Stacked Bar Graphs
Data Visualization:
100% Stacked Bar Graphs
Data Visualization:
Stacked Area Charts
Data Visualization:
Line Charts
Data Visualization:
Pie Charts
Data Visualization:
Scatter Plots
Data Visualization:
Clustered Scatter Plots
Data Visualization:
Bubble Charts
Data Visualization:
Heat Maps
Data Visualization:
Cloropleth (Filled Map)
Data Visualization:
Dot Maps
Data Visualization:
Treemaps
Data Visualization:
Dual-Axis Graphs
