Question

Express the following constraints about the relations of Exercise 1, reproduced here:

a)Product (maker, model, type)
b)PC (model, speed, ram, hd, price)
c)Laptop (model, speed, ram, hd, screen, price)
d)Printer (model, color, type, price) You may write your constraints by equating an expression of relational algebra to the empty set. For the data of Exercise 2, indicate any violations to your constraints.
(a) A PC with a processor speed less than 2.00 must not sell for more than $500. (9%)

Answer 1

Constraints in relational databases ensure that data adheres to certain rules. In the given scenario, PCs with speeds less than 2.00 should not be priced above $500. For real-world purchasing decisions, verifying claims about a product's price variability can lead to better-informed choices.

Step-by-step explanation:

When it comes to relational database constraints, particularly in the context of Exercise 1, we are looking at setting rules that govern the allowable data in the database. In the scenario provided, we have a specific constraint for PC prices relative to their processor speeds. The expression of this requirement using relational algebra might look like this:

speed < 2.00 and price > 500 = {}

This means that there should be no PC with a speed less than 2.00 that is selling for more than $500; the set of such PCs should be empty. Without data from Exercise 2, we cannot concretely identify violations, but any PC listed with a speed below 2.00 and a price above $500 would be in violation of this constraint.

Concerning real-world purchases, such as buying a computer, when faced with claims of pricing standard deviations, customers can conduct a hypothesis test to verify such claims. A larger standard deviation than claimed would suggest more variability in pricing than expected. In practical terms, if a larger standard deviation is found, it could mean that searching for a better deal might yield more significant savings than initially thought.