Statistics Chapter 2 Flashcards

Center of Data

• Represents the middle or average value of a data set.
• Indicates distribution centrality.

Variation

• Measures the degree to which data values differ from each other.
• Important in understanding data consistency and spread.

Distribution

• Refers to the shape or nature of the data set.
• Provides insights into how data points are spread across different values.

Outliers

• Values that are significantly distant from the majority in a data set.
• Can skew analysis and results if not accounted for.

Time

• Represents changes in data characteristics over intervals.
• Vital for trend analysis and historical comparisons.

Frequency Table (Frequency Distribution)

• Organizes data values with their corresponding frequencies.
• Can be presented as individual values or grouped intervals.

Lower Class Limits

• The smallest values that can belong to a class in a frequency distribution.
• Essential for defining intervals in grouped data.

Upper Class Limits

• The largest values that can belong to a class in a frequency distribution.
• Used to set boundaries for data categorization.

Class Width

• Calculated as the difference between consecutive lower class limits.
• Helps in establishing uniform intervals for data classification.

Class Boundaries

• Separate class intervals without gaps from class limits.
• Designed to enhance clarity in data representation.

Class Midpoints

• Calculated as the average of the lower and upper class limits for each class.
• Provides a representative value for the class to simplify analyses.

Procedure for Constructing a Frequency Distribution

• Determine a suitable number of classes (5 to 20 is ideal).
• Calculate class width and round for convenience, ensuring simplicity in interpretation.

Summary of Service Times Example

• Total individuals included: 52 (sum of frequencies).
• Exact service times cannot be identified; original values could fall anywhere within their respective class limits.

Normal Distribution Flaws

• Relative frequencies should not be uniform; ideally, they should form a bell curve.
• Total relative frequency must sum to 100%, indicating an error (sum is 123%).

Frequency Distribution Example Identification

• Lower class limits: 10, 15, 20, 25, 30, 35, 40.
• Upper class limits: 14, 19, 24, 29, 34, 39, 44.
• Class width: 5, calculated from the difference between limits.
• Class midpoints calculated for each interval.
• Class boundaries identified for enhanced data separation.
• Total number of individuals included: 87 (sum of frequencies).