Font size
WorksheetsBusiness Computation
Total questions: 20
Worksheet time: 18mins
Which one of the following survey questions would generate numerical data?
What is your favourite colour?
What type of car does your family own?
How long does it take for you to travel to school?
What type of dog do you own?
Which one of the following survey questions would generate categorical data?
Which is your favourite fast food?
How many times do you eat at your favourite fast-food place in a typical week?
How much do you usually spend buying your favourite fast food?
How many items did you buy last time you went to your favourite fast food place?
If you asked 20 people their favorite color, why would mode best represent the data?
You cannot find the mean or median of colors.
You are likely to get repeated data.
The data is categorical, not numerical.
all of the above
What type of graph shows change over time?
Circle Graph
Trend Graph
Bar Graph
Line Graph
Bar graphs are used to best represent what type of data?
Change over Time
Trends over Time
Categories of Information(Comparisons)
Percentages
The table shows the production, imports and consumption of electricity of a certain state. Pick the appropriate bar graph that represents the statistics in the data table.
Graph 1
Graph 2
Graph 3
Graph 4
If you were the owner of Shop A, what flavors of ice cream do you want to make sure that you have on hand?
chocolate
coconut
mango
chocolate and mango
As a farmer, you will need to hire additional people to help harvest the crops. What month will you need the most help?
February
June
March
May
A popular restaurant likes to keep track of what food their patrons are ordering so that they can be better informed about what items they need to order in preparation for the next week. What would be the best way for the restaurant to organize this data with that end goal in mind?
List what meat, vegetable and fruit each customer ordered (steak - corn - apples, fish - peas - peaches, etc).
Record the exact name of the meal that was ordered (Dave’s Famous Wings, Southwest Bacon Burger, Grilled Chicken Panini, etc).
Keep track of what was ordered by the category that they fall under (Entree, Dinner, Appetizer, Salad, etc).
Record the cost of each meal purchased and whether the customer got the meal as-is or substituted some items.
A local high school recently won the girls volleyball championships and have been rewarded by the school with $5,000 to purchase merchandise for the team. The coach is trying to surprise the players with the merchandise at the banquet, so instead of asking them what sizes they want, he is trying to figure that out based on the information from the volleyball program. The following information is stored in the program for each player.
What would be the best way for the coach to use this information in order to order sizes that work for the majority of the team?
Filter the data by grade and order larges for the juniors and seniors, mediums for the sophomores and smalls for the freshmen.
Sort the data by jersey number, ordering smaller sizes for the lower numbers and larger sizes for higher numbers.
Sort the data by height and weight and order smaller sizes for the girls that are shorter and weigh less and order larger sizes for the girls that are taller and weigh more.
Filter the data by age and height, where the older and taller girls will get larger sizes and the younger and shorter girls will get smaller sizes.
Students are using data collected from a non-profit organization in order to try to convince the school board that their school should be year-round with several week long breaks as opposed to the usual 9 months on and 3 months off. Information that was collected by this organization was as follows.
They decided to make an infographic in order to try to easily display the data they have analyzed. Which of the following would be the best information to put on their infographic to try to convince the school board of the change to the schedule?
Select two answers.
A cluster analysis of where year-round schools and regular schools are located geographically.
An association rule showing links between motivation and happiness levels to the type of schooling students were receiving.
A regression analysis of standardized tests scores comparing the two different types of schooling.
An automated summarization of student handbooks from year round schools, displayed in a word cloud.
The following statements are TRUE of data cleaning:
Duplicates and unwanted observations should be removed.
Data visualising can be used to pull out the unwanted data.
Data imputation is used to deal with missing values.
Clean data needs complex operations to produce insights.
Outliers can cause problems to model and thus, should be always removed.
This is the way to explain the notation X-->Y: A rule ( X--> Y) means that the rise in sales of X leads to a rise in sales in Y.
true
false
Confidence of a rule X-->Y measures the strength of correlation of two variables.
true
false
High support for rule X-->Y implies high confidence for the rule too.
true
false
If a lift of a rule (X --> Y) is less than 1, it means that it is less likely to find the items in Y in those transaction which has items in X than a randomly selected transaction containing Y.
true
false
The goal of clustering a set of data is to
divide them into groups of data that are near each other
choose the best data from the set
determine the nearest neighbours of each of the data
predict the class of data
Which of the following statements are true?
It is impossible to cluster objects in a data stream. We must have all the data objects that we need to cluster ready before clustering can be performed.
When clustering, we want to put two dissimilar data objects into the same cluster.
Clustering analysis in unsupervised learning since it does not require labeled training data.
Clustering analysis has a wide range of applications in tasks such as data summarization, dynamic trend detection, multimedia analysis, and biological network analysis.
What do we need to do with data to derive decisions from them?
Transform the data in diagrams
Transform data into lists
Transform data into Excel sheets
Transform data into smart data
Business analytics framework consist of
Descriptive analytics; predictive analytics; prescriptive analytics
Data mining; data cleaning; analytics
Inferential statistics; knowledge discovery; data warehouse; reporting
Data, database, information, report
