Data And Information

Front 1

What are the phases of Database Design?

Back 1

Conceptual, Logical, Physical

Front 2

Name the steps of conceptual design phase.

Back 2

1. Identify entities
2. Identify relationships
3. Identify and associate attributes with entities and relationships
4.Determine attribute domains
5.Determine candidate, primary, and alternate key attributes
6.Specialize/generalize entities (optional)
7.Check the model for redundancy
8.Check that the model supports user transactions
9.Review the conceptual database design with users

Front 3

Explain superkey, candidate, primary, and alternate keys.

Back 3

Superkey - a set of columns that uniquely identifies a record in a table.
Candidate key - superkey with only the minimum columns necessary for identification.
Primary key - candidate key chosen for unique id of records.
Alternate - not chosen candidate key.

Front 4

Explain strong/weak entities.

Back 4

Strong have their own primary key. Weak depends on other entities for unique identification.

Front 5

What is Significance level? What is its threshold.

Back 5

Probability that the relationship is due to chance. p < 0.05

Front 6

Explain the difference between patent and copyright.

Back 6

Copyright - automatic, protects manifestation of idea, not the idea itself. Covers software.
Patent - protects the idea behind the invention, needs to be applied for, software and many mental proccesses are not patentable.

Front 7

What is Triangulation?

Back 7

Data obtained using various research methods.

Front 8

What is reliability of research?

Back 8

Replicability. "Will we get the same result each time we measure?"

Front 9

What is validity of research?

Back 9

"Are we actually measuring what we claim to be measuring?"

Front 10

Types of measurements :

Back 10

Scale ( quantitative)
- in rank order, equal intervals, ratio
Ordinal(qualitative)
example:Likert scale
- rank order, no interval and ratios
Nominal(categorical)
- for grouping
Example: 1- single, 2 - married etc.

Front 11

Describe measures of central tendency.

Back 11

Mean - average
Median - middle value
Mode - most common value

Front 12

Describe measure of normality.

Back 12

Kurtosis - peakedness, pos. values cluster around center, neg. flat distribution.
Skewness - symmetry. Pos. more low value (skewed tow. left), neg. more high values (right).
Mean and St.D. should not be used if distribution is not normal.

Front 13

What is correlation? What test measures it?

Back 13

Extent to which 2 variables co-vary.
Can be measured by Pearson's Product-Moment Correlation, parametric test. (r)

Front 14

Describe measures of dispersion.

Back 14

Range - from min to max
Standard deviation - avg. difference from sample mean. In a normal distribution 68% of values lie within 1 SD of mean, 95% - 2 SD.

Front 15

Independent - dependent variables.

Back 15

Independent variable believed to affect the dependent variable.
Example:
coffee consumption(IV) --> insomnia(DV)

Front 16

When parametric tests can be used?

Back 16

When:
Distributions are normal.
Variances are equivalent.
Measurements are on a continuos scale.

Front 17

What test is used to measure the Difference?

Back 17

T - test.
0.01 - small effect
0.06 - moderate effect
0.14 - large effect

Front 18

What is a DBMS? Examples.

Back 18

Database Management System. An application that allows users to interact with the database.

Front 19

Describe a three-tier database model.

Back 19

User interface layer. (the client)
Business logic and data processing layer ( the application server).
DBMS (the database server) distributed over different machines.

Front 20

Describe the three levels of abstraction in ANSI-SPARC database architecture.

Back 20

External level - Different User views.
Conceptual level - community view.
Internal level - computer's view.

Front 21

What is database schema and database instance?

Back 21

Schema - description of the database structure.
Instance - data in the database at a particular point in time.

Front 22

Explain data independence.

Back 22

Immunity of schemas to changes in different level schemas.

Front 23

Explain entity integrity.

Back 23

It is a constraint that states that in a base table no column of a primary key can be null.

Front 24

Explain referential integrity.

Back 24

Constraint that states that foreign key values must match a candidate key value of some record in the home(parent) table or be wholly null.

Front 25

Explain functional and transitive dependencies.

Back 25

fd - X --> Y , for every X there is only 1 Y, but for every Y may be several X. td - if X --> Y --> Z then Z is transitively dependent on X.

Front 26

What are the most common fact-finding techniques.

Back 26

Examining documentation.
Interviewing.
Observation.
Secondary research.
Questionnaires.

Front 27

What is the degree of a relationship? Provide examples.

Back 27

Number of participating entities. Can be unary(recursive), binary, ternary etc.

Front 28

Explain simple, composite, derived attributes.

Back 28

Single component/ multiple component/ calculated from a different attribute.

Front 29

What is an entity?

Back 29

A set of objects with the same properties that are identified as having an independent existence.

Front 30

Explain multiplicity, cardinality and participation.

Back 30

Number of entity occurrences that relate to other entity occurrences through a particular relationship / number of possible relationships for each participating entity (maximum) / describes whether all or only some entity occurrences participate in a relationship (minimum).

Front 31

Explain first, second and third normal forms.

Back 31

1NF - no intersection of column and record may contain more than 1 value
2NF - applies only to tables with composite primary key, all columns must be determined by values in ALL the columns that make up primary key.
3NF - all non-primary key values must be determined ONLY by the primary key column(s) and no others.

Front 32

What is normalization?

Back 32

Technique for producing a set of tables with minimal redundancy and therefore guards from update anomalies.

Front 33

Explain Foreign key, parent, child.

Back 33

Foreign key is a column within one table that is also the candidate key of another table. Child tables are those that contain foreign keys that link to the parent table.

Front 34

Explain specialization and generalization.

Back 34

Specialization is the process of maximizing the differences between members of an entity by identifying their distinguishing characteristics.
Generalization is the opposite (minimizing differences by finding common features)

Front 35

What constraints may apply on a superclass/subclass relationship?

Back 35

Participation - Optional/Mandatory, determines if every occurrence of a superclass must be a member of a subclass.
Disjoint constraint - Or/And, possibility of being a member of multiple subclasses.

Front 36

What is the purpose of logical database design phase?

Back 36

To describe a set of tables based on the ER model created in conceptual phase.

Front 37

Steps of logical database design phase.

Back 37

Create tables.
Check table structures using normalization.
Check that the tables support user transactions.
Check integrity constraints.
Review the logical database design with users.

Front 38

When these tests are used?
ANOVA, Paired t-test, Chi-square, Independent t-test, Mann-Whitney, Wilcoxon Signed Ranks

Back 38

ANOVA - when there are more than two groups and variables
Mann-Whitney - non-parametric equivalent of independent t-test
Paired t-test - parametric test to use on the same sample (i.e. before - after treatment)
Wilcoxon Signed Ranks - non-parametric equivalent of paired t-test
Independent t-test - parametric difference test on two different samples
Chi-square is used for nominal or frequency data