Statistical Reasoning Exam 1 Topics

Population

particular group of individuals being studied

Target population

determined by sampling criteria

Accessible population

sample within target population

Study elements

individuals or items from the accessible population that are included in a study.

Sample size

must be of adequate size to determine significant relationships among variables or differences between groupsin order to enhance the reliability and validity of the study's findings.

4 elements to power analysis

Alpha or level of significance, standard power, effect size, sample size

Alpha or level of significance

Usually 0.05

Standard power

usually 0.80 or 80%

Refusal Rate formula

(number refusing to participate / number approached) x 100

Attrition rate

percentage of students dropping out of a study after sample size has been determined based on sampling criteria

Attrition rate formula

(number dropping out / total sample size) x 100

Nominal

data categories must be exclusive, must be exhaustive. Ex. gender, race/ethnicity

Ordinal

data categories that can be ranked or ordered but have no defined distance between categories. Ex. education level, satisfaction ratings.

Interval

data that can be ordered with defined distances between categories, but no true zero point. Ex. temperature in Celsius or Fahrenheit.

Ratio

data categories with a true zero point, allowing for comparison of absolute magnitudes. Ex. height, weight, temperature in Kelvin.

Probability Sampling

Every member of the study population has an equal independent opportunity to be chosen for inclusion

Sampling frame

each person or element in a study target population and randomly selecting a sample from that population

Simple random sampling

occurs through a random selection of members from the sampling frame

Stratified random sampling

used when researcher knows some of the variables within a population that will affect the representativeness of the sample

Cluster (Complex) Sampling

used when specific elements of a population are unknown making it impossible to develop the sampling frame

Systematic Sampling

selected through a process that accepts every kth member on the list using a randomly selected starting point

Nonprobability Sampling

does not extend an equal opportunity for selection to all members of the study population

Convenience sampling

enroll subjects who are accessible and available to participate in the study

Quota sampling

used to ensure adequate representation of all types of subjects who are likely to be underrepresented

Purposive sampling

occurs when the researcher consciously selects subjects, elements, events or incidents to include in the study

Network sampling

use of social networks

Theoretical sampling

used in research process to advance development of a theory and is more commonly used in grounded theory studies

Stability Reliability

consistency of repeated measures of the same variable or attribute with the same scale or measurement method over time

Equivalence Reliability

compares two versions of the same scale or instrument or two observers measuring the same event

Internal Consistency / Homogeneity Testing

examines the extent to which all the items in a multiple-item instrument or scale consistently measure a variable

Cronbach’s Alpha

a statistic used to assess the internal consistency or reliability of a set of scale or test items.

Mean

the average value of a set of numbers, calculated by dividing the sum of all values by the number of values.

Mode

the value that appears most frequently in a data set.

Median

the middle value in a dataset when it is ordered from least to greatest, or the average of the two middle numbers if there is an even number of observations.