Chapter A (Basic Statistical Concepts) Flashcards
A body of knowledge (science) that deals
with the following methods:
Statistics
Collection
Organization
Presentation
Analyzation
Interpretation of Data
COPAIData
is a set of numerical figures
Statistics
Six uses of Statistics
- Describe the general characteristics of the collection of elements under study called the population
- Compare different subpopulations
- Explain a phenomenon that has taken place in the population
- Predict future phenomena that will take place in the population
- Describe the relationships between the
different characteristics of the elements in
the population - Study cause-and-effect
DCEPDS
Population vs. Sample
Population is the collection of all the elements under consideration in any
statistical study and answers “who
do you want to study?” while Sample is part (or subset) of the population from which information is collected
Variable vs. Observation vs. Data
- Variable a characteristic or an attribute of the elements in a collection that can assume different values for different elements (answers: what do you want to measure or observe?)
- Observation realized value of a variable
- Data is the collection of observations
Two Types of Variable
Quantitative and Qualitative Variable
have labels or names assigned to their
respective categories
Qualitative Variable
any characteristic that can be measured or
counted in numbers
Quantitative Variable
the process of determining the value or label of a particular variable for a particular element based on what has been observed
Measurement
Four Levels of Measurement
NOIR
1. Nominal
2. Ordinal
3. Interval
4. Ratio
- The numbers in the measurement system are used to classify an element into distinct, nonoverlapping, and exhaustive categories (D, N-O, E)
- Categories are of equal importance
Nominal
Example:
1. Sex of students (1 – Male, 2 – Female)
2. Favorite color of women
3. Support for marijuana legalization (Yes, No)
- The numbers in the measurement system are used to classify an element into distinct categories (D C)
- The system arranges the categories according to magnitude (ordering matters) (M - O)
Ordinal
Example:
1. UP student classification (Fr, So, Jr, Sr)
2. Birth order (First born, second born, etc.)
- The numbers in the measurement system are used to classify an element into distinct categories
- The system arranges the categories according to the magnitude
- The system has a fixed unit of measurement representing a set size throughout the scale
- The system has no true zero
Interval
Examples:
1. Daily maximum temperature (in Celsius)
2. Time in military hours
3. Intelligent Quotient Score
The numbers in the measurement system are used to classify an element into distinct categories
- The system arranges the categories according to the magnitude
- The system has a fixed unit of measurement representing a set size throughout the scale
-The system has an absolute zero
Ratio
Examples:
1. Number of cups of rice consumed per meal
2. Length of service (in years) of employees
3. Household size
What levels of measurement are for Qualitative and Quantitative
Qualitative
Nominal
Ordinal
Quantitative
Interval
Ratio
Importance of Levels of Measurement
The level of measurement is one of the
considerations in choosing the appropriate statistical tool to analyze the data
1. Nominal (equality)
2. Ordinal (greater than or less than)
3. Interval (difference or sum)
4. Ratio (all algebraic operations)
Parameter vs. Statistic
Parameter
- a summary measure describing a
specific characteristic of the
population
Statistic
- a summary measure describing a
specific characteristic of the sample
- a summary measure describing a
specific characteristic of the sample
Statistic
- a summary measure describing a
specific characteristic of the
population
Parameter
Two Major Areas in Statistics
Descriptive and Inferential
includes all the techniques used in organizing, summarizing, and presenting the data on hand collected from either sample or a population
Descriptive Statistics
includes all the techniques used in analyzing the sample data that will lead to generalizations about a population from which the sample came from
Inferential Statistics
Using samples can still be descriptive statistics in the sense that no generalization is made for the entire population but instead the results only aim to describe/characterize the samples.
True
Descriptive or Inferential?
A sociologist interviewed a random sample of 50 UPLB students to determine whether they can handle stress or not. Results found that the majority of all UPLB students cannot handle their stress alone and need strong social support.
Inferential
