Basic Stat: General Terms, Sample and Sampling Distribution
May 28, 2014
MODULE 1: BASIC CONCEPTS IN STATISTICS
1. Variable = any representation of any event, situation, phenomenon, object or person defined by a set of characteristics
2. Independent Variable (IV) – sometimes known as the “cause or input” variable; it is the variable that is being controlled or manipulated
3. Dependent Variable (DV) – sometimes called the “effect or output” variable, whose change is dependent on the change in the IV.
4. Discrete Variable – a variable which assumes finite value as countable variable
5. Continuous Variable – a variable which takes infinite values within a range continuum
6. Population (N) = the totality or aggregate of any variable at a certain point of reference
7. Sample (n) = the proportion or fraction of the population at a certain point of reference
8. Parameter – the value derived from the population
9. Statistic(s) – the value(s) derived from sample
10. Measurement – the process of quantifying any variable
11. Levels/Scales of Measurement
a. Nominal – utilized for categorical data which uses coding and decoding techniques
i.
b. Ordinal – uses ranking system
i. 1st, 2nd, 3rd ii. Youngest to oldest
c. Interval – uses fixed amount or value, with no absolute zero value, from one point to another which sets the consistency of data distribution
i. 5, 10, 15… ii. 30, 40, 50
d. Ratio – resembles similar characteristics with interval, except that there exists an ‘absolute zero-value’
June 4, 2013
MODULE 2: SAMPLE AND SAMPLING DISTRIBUTION
Sample - any representation as a portion of the population this is used to conserve MET (money, effort, and time)
Slovin’s Formula – used to determine the “ideal” sample size (n)
Ex.
N = 1000 e = 0.05
Where;
= population size
= sample size
1 = whole (constant) e = margin of error
Most commonly used e:
a) 0.01 = medical-health related fields *life and death consequences
b) 0.05 = allied fields
MODULE 1: BASIC CONCEPTS IN STATISTICS
1. Variable = any representation of any event, situation, phenomenon, object or person defined by a set of characteristics
2. Independent Variable (IV) – sometimes known as the “cause or input” variable; it is the variable that is being controlled or manipulated
3. Dependent Variable (DV) – sometimes called the “effect or output” variable, whose change is dependent on the change in the IV.
4. Discrete Variable – a variable which assumes finite value as countable variable
5. Continuous Variable – a variable which takes infinite values within a range continuum
6. Population (N) = the totality or aggregate of any variable at a certain point of reference
7. Sample (n) = the proportion or fraction of the population at a certain point of reference
8. Parameter – the value derived from the population
9. Statistic(s) – the value(s) derived from sample
10. Measurement – the process of quantifying any variable
11. Levels/Scales of Measurement
a. Nominal – utilized for categorical data which uses coding and decoding techniques
i.
b. Ordinal – uses ranking system
i. 1st, 2nd, 3rd ii. Youngest to oldest
c. Interval – uses fixed amount or value, with no absolute zero value, from one point to another which sets the consistency of data distribution
i. 5, 10, 15… ii. 30, 40, 50
d. Ratio – resembles similar characteristics with interval, except that there exists an ‘absolute zero-value’
June 4, 2013
MODULE 2: SAMPLE AND SAMPLING DISTRIBUTION
Sample - any representation as a portion of the population this is used to conserve MET (money, effort, and time)
Slovin’s Formula – used to determine the “ideal” sample size (n)
Ex.
N = 1000 e = 0.05
Where;
= population size
= sample size
1 = whole (constant) e = margin of error
Most commonly used e:
a) 0.01 = medical-health related fields *life and death consequences
b) 0.05 = allied fields