Figuer:
CUSTOMER In Table CUSTOMER, CID Is the Primary Key (Customer ID)

question 25

Multiple Choice

Figuer:
CUSTOMER $$\begin{array} { | l | l | l | l | l | } \hline \text { CID } & \text { CNAME } & \text { AGE } & \text { RESID\_CITY } & \text { BIRTHPLACE } \\\hline 10 & \text { BLACK } & 40 & \text { ERIE } & \text { TAMPA } \\\hline 20 & \text { GREEN } & 25 & \text { CARY } & \text { ERIE } \\\hline 30 & \text { JONES } & 30 & \text { HEMET } & \text { TAMPA } \\\hline 40 & \text { MARTIN } & 35 & \text { HEMET } & \text { TAMPA } \\\hline 50 & \text { SIMON } & 22 & \text { ERIE } & \text { ERIE } \\\hline 60 & \text { VERNON } & 60 & \text { CARY } & \text { CARY } \\\hline\end{array}$$ In table CUSTOMER, CID is the primary key (Customer ID) .
RENTALS $$\begin{array} { | l | l | l | l | l | l | } \hline \text { CID } & \text { MAKE } & \text { DATE\_OUT } & \text { PICKUP } & \text { RETURN } & \text { RTN } \\\hline 10 & \text { FORD } & 10 - 0 c t - 1994 & \text { CARY } & \text { CARY } & 1 \\\hline 10 & \text { GM } & 01 - N o v - 1995 & \text { TAMPA } & \text { CARY } & 2 \\\hline 10 & \text { FORD } & 01 - J a n - 1995 & \text { ERIE } & \text { ERIE } & 3 \\\hline 20 & \text { NISSAN } & 07 - J u 1 - 1994 & \text { TAMPA } & \text { TAMPA } & 4 \\\hline 30 & \text { FORD } & 01 - J u l - 1995 & \text { CARY } & \text { ERIE } & 5 \\\hline 30 & \text { GM } & 01 - A u g - 1995 & \text { ERIE } & \text { ERIE } & 6 \\\hline 40 & \text { FORD } & 01 - A u g - 1994 & \text { CARY } & \text { ERIE } & 7 \\\hline 50 & \text { GM } & 01 - S e p - 19 95 & \text { ERIE } & \text { CARY } & 8 \\\hline 70 & \text { TOYOTA } & 02 - S e p - 1995 & \text { RENO } & \text { RENO } & 9 \\\hline\end{array}$$ In the table RENTALS, RTN provides the rental number (the primary key) , CID is the customer's unique id, PICKUP is the city where the car was picked up, and Return is the city where the car was returned.
RENTCOST $$\begin{array} { | l | l | } \hline \text { MAKE } & \text { COST } \\\hline \text { FORD } & 30 \\\hline \text { GM } & 40 \\\hline \text { NISSAN } & 30 \\\hline \text { TOYOTA } & 20 \\\hline \text { VOLVO } & 50 \\\hline\end{array}$$ RENTCOST shows the base cost of renting a given MAKE for one day.
CITYADJ $$\begin{array} { | l | l | } \hline \text { CITY } & \text { FACTOR } \\\hline \text { CARY } & 1 \\\hline \text { ERIE } & 1.1 \\\hline \text { RENO } & 0.9 \\\hline \text { TAMPA } & 0.8 \\\hline\end{array}$$ If the return city of table RENTALS is the one listed in table CITYADJ, the cost of the rental is multiplied by FACTOR and by DAYS shown in table RENTLENGTH below.
RENTLENGTH $$\begin{array} { | l | l | } \hline \text { RTN } & \text { DAYS } \\\hline 1 & 1 \\\hline 2 & 3 \\\hline 3 & 2 \\\hline 4 & 2 \\\hline 5 & 4 \\\hline 6 & 2 \\\hline 7 & 3 \\\hline 8 & 1 \\\hline\end{array}$$ RENTLENGTH shows the number of days for the rental number (RTN) shown in table RENTALS. In a database used in reality, this table would be merged with the RENTALS table.
-SELECT MAKE FROM RENTALS,CUSTOMER
WHERE RENTALS.CID = CUSTOMER.CID
AND RESID_CITY = 'HEMET'
GROUP BY MAKE
HAVING COUNT (DISTINCT RENTALS.CID) =
(SELECT COUNT(*) FROM CUSTOMER
WHERE RESID_CITY = 'HEMET')
The execution of this query produces the following number of rows:

• A) 0
• B) 1
• C) 2
• D) 3

Differentiate between different types of probability distributions.

Calculate cutoff values for specific percentiles in a normal distribution.

Understand and apply concepts of the exponential distribution in context.

Perform probability calculations for both sides of the mean in a normal distribution.

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Definitions:

Law of Effect

Law stating that if an action is followed by a pleasurable consequence, it will tend to be repeated, and if followed by an unpleasant consequence, it will tend not to be repeated.

Thorndike

An American psychologist who developed the law of effect and is known for his work in learning theory and educational psychology.

Operant Conditioning

A type of learning where behavior is controlled by consequences, including rewards for positive actions and punishments for negative actions.

Reinforcement

A concept in behavioral psychology where a behavior becomes more likely to occur due to the consequence that follows it.