lec 3(done)

Question 1

Data objects

Answer 1

represents an entity.
ex.
1-Sales database: customers, store items, sales
2-Medical database: patients, treatments
3-University database: students, professors, courses

Question 2

Attribute:

Answer 2

a data field, representing a characteristic or feature of a data object.

Question 3

Attribute Types:

Answer 3

1-Nominal
2-Binary
3-Ordinal
4-Numeric

Question 4

nominal attribute:

Answer 4

-Each value represents some kind of category, so nominal attributes are also called categorical.
-The values do not have any meaningful order.
ex.
-Hair_color = {black, blond, brown, grey, red, white}
-marital status, occupation, ID numbers, zip codes

Question 5

Binary Attributes:

Answer 5

Nominal attribute with only two categories or states (0 and 1)

Symmetric binary: both outcomes equally important
Example: gender: {male, female}

Asymmetric binary: outcomes not equally important.
Example: medical_test {positive, negative}

Question 6

Ordinal Attributes:

Answer 6

Values have a meaningful order (ranking) but magnitude between successive values is not known.

Examples:
Size = {small, medium, large}
grades, army rankings, satisfaction level

Question 7

Numeric Attributes

Answer 7

Quantitative (integer or real-valued)
1-Interval-Scaled
-The differences between values are meaningful
-No true zero-point
-Values have order and can be positive, 0, or negative
Examples: temperature in C˚or F˚, calendar dates

2-Ratio-Scaled
-The differences and ratios between values are meaningful
-True zero-point
-Values are ordered
Examples: age, counts, height, weight, speed, monetary quantities

Question 8

Attribute type with operations

Answer 8

slide 9

Question 9

Discrete Attribute:

Answer 9

1-Has a finite or countably infinite set of values
2-Sometimes, represented as integer variables
Examples: hair color,zip codes, smoker, anddrink size

Question 10

Continuous Attribute:

Answer 10

1-Has real numbers as attribute values
2-Typically represented as floating-point variables
Examples: temperature, height, or weight

Question 11

Measuring the central tendency:

Answer 11

Mean, Median, Mode, Midrange

Question 12

Measuring the dispersion of data:

Answer 12

1-Variance
2-Standard Deviation
3-Range
 4-Quantiles
 5-Interquartile Range
 6-Five-Number Summary
 7-Boxplots.

Question 13

Graphic displays of basic statistical descriptions of data:

Answer 13

1-Quantile Plot
2-Quantile-Quantile Plot
3-Histograms
4-Scatter plots

Question 14

Arithmetic mean

Weighted arithmetic mean

Trimmed mean

Answer 14

slide 13

Question 15

Median:

Answer 15

Middle value if odd number of values, or average of the middle two values otherwise.

Question 16

Mode:

Answer 16

Value that occurs most frequently in the data

Data sets with one, two, or three modes are respectively called unimodal , bimodal , and trimodal.

Question 17

Midrange:

Answer 17

Average of the smallest and largest values in the set.