BE LEC FINAL

• Data - raw material of statistics
• Data - values that the variables can assume
• Data set - collection of data values
• Data set - each value in the data set (data value or a datum)
• Sources of data - suitable data to serve as the raw material for our investigation
• Statistics - science of conducting studies to collect, organize, summarize, analyze, and draw conclusions from data
• Biostatistics - when data analyzed are derived from the biological sciences, medicines, and public health
• Purpose of Statistics

  to investigate and evaluate the nature and meaning of information contained in number (data)
• Descriptive Statistics - consists of the collection, organization, summarization, and presentation of data.
• Inferential Statistics - consists of generalizing from samples to populations, performing estimations, probabilities, hypothesis testing, determining relationships among variables, and making predictions.
• Population (collection of entities) - consist of all subjects (human, animals, machines, places) being studies for which we have an interest at a particular time
• Finite - Can be measure/counted
• Infinite - cannot be measured/counted
• Sample - group of subjects or entities selected from a population
• Variable - A characteristics or attribute that assumes different values
• KIND OF VARIABLE

  Quantitative - age, height, weight, body temperatures
• KIND OF VARIABLES

  Qualitative - gender, religion, geographic location
• KIND OF VARIABLE

  Random - occurs by chance; cannot be predicted
• SUBGROUPS OF QUANTITATIVE

  Discrete Variable (Finite) - assume values that can be counted (0,1,2,3)

  eg. number of children in a family, number of students in a classroom
• SUBGROUPS OF QUANTITATIVE

  Continuous Variable (Infinite) - can assume an infinite number of values in an interval between any two specific values

  eg. temperature, length, mass, time
• CONTINOUS VARIABLE

  Answers must be rounded because of the limits of a measuring device (usually to the nearest given unit)
• Nominal Level - No rank or order can be placed on the data

  mutually exclusive or collectively exhaustive)

  eg. a sample of college instructors classified according to subjects taught (English, history, science)
• Ordinal Level - can be placed into categories; can be ordered or ranked

  precise measurements between ranks do not exist

  eg. Student evalutions (superior, average, poor)
• Interval Level - precise distance or differences DO exists between units

  on property lacking: no true zero value
• Ratio Level - relationship between two numbers

  have differences between units (1 inch, 1 pound)

  exists a trust zero value or true ration between values
• Systematic Sampling - numbering each subject of the population then selecting every kth subject
• Random Sampling - Selected by using chance methods or random number
• Stratified Sampling - obtained by dividing the population into groups (strata) according to some characteristics
• CLASSIFICATION OF STATISTICAL STUDIES

  Observational studies - researchers merely observes what is happening or what has happened in the past and tries to draw conclusions based on these observations
• CLASSIFICATION OF STATISTICAL STUDIES

  Experimental studies - researcher manipulate one of the variables and tries to determine how the manipulation influences other variables
• TYPE OF RESEARCH VARIABLES

  Independent variable - also known as explanatory variable

  variable that is manipulated by the researcher
• TYPE OF RESEARCH VARIABLES

  Dependent Variables - resultant variable or the outcome variable

  Variable being studied to see if it has changed significantly due to manipulation of the independent variable
• Mean - arithmetic average

  • adding values of the data and dividing the total number of values
• Median - halfway point in a data set

  • date needs to be ordered (data array) as a requirement to find the median
• Outlier - An extremely high or low data value in a data set
• Midrange - a rough estimate of the middle

  rough estimate of the average

  found by adding the lowest and highest values in data set and dividing 2
• Weighted Mean - mean of a data set in which not all values are equally represented
• Mode - used when the most typical case is desired
• Variance - the average of the square of the distance each value from the mean is from the mean
• Standard deviation - the square root of the variance