Research 2

• Statistics


  The science of collecting, organizing, presenting, analyzing, and interpreting numerical data to assist in making more effective decisions
• Statistic


  A characteristic of a sample (mean, standard deviation, variance, or any other measure based on a sample data)
• Why study statistics


  • To scientifically measure conditions of any given problem and assess existing relationship(s)
  • To show the laws underlying facts and events that cannot be determined by individual observations
  • To reveal cause and effect relations that otherwise may remain unknown
  • To uncover ambiguous trends and behavior in related conditions
• Uses and applications of statistics

  • Marketing
  • Accounting
  • Business
  • Quality control
  • Politics
  • Sports
  • Health administration
  • Education
• Descriptive statistics


  The method of organizing, summarizing, and providing a description of the sample data in an informative way
• Descriptive statistics


  • Presenting data in percentage, ranks, standard units, frequency distribution, measures of location, measures of dispersion
• Inferential statistics


  Used to infer the truth or falsity of a hypothesis, make a decision, estimate, prediction, or generalization about a population based on a sample
• Population (N)


  A collection of possible individuals, objects, elements, or measurements of interest
• Sample (n)


  A portion, or part, of the population of interest
• Population and sample


  • N = 296 3rd year nursing students
  • n = 72 students selected to participate in the survey
• Non-parametric statistics


  The branch of statistics wherein the gathered data to be analyzed are not required to fit a normal distribution
• Non-parametric statistics


  • Use data that are often ordinal, do not rely on number but rather a ranking or order, can be used without the mean, sample size, standard deviation, or the estimation of any other related parameters
• Parametric statistics


  The branch of statistics concerned with data measurable on interval or ratio scales and the sample size is appropriate, so that arithmetic operations are applicable to them, enabling parameters such as the mean of the distribution to be defined
• Parametric vs non-parametric


  If your measurement scale is nominal or ordinal then you use non-parametric statistics, if you are using interval or ratio scales, you use parametric statistics
• Qualitative or attribute variable


  The characteristic or variable being studied is nonnumeric
• Qualitative variables


  • Gender, religious affiliation, type of automobile owned, place of birth, hair color
• Quantitative variable


  The variable can be reported numerically
• Discrete variable


  Can only assume certain values and there are usually "gaps" between values, typically result from counting
• Discrete variables


  • Number of chairs in a classroom, number of cars exiting the University main gate over an hour, number of students in each section of graduate Statistics class, number of children in a family
• Continuous variable


  Can assume any value within a specific range
• Continuous variables


  • Time it takes to fly from Cebu to Manila, air pressure in a tire, weight of a shipment of grains, distance between Cebu and Bohol, balance in your checking account, minutes remaining in class
• Datum


  One information
• Data


  Many information, known facts, figures, observations, statistics, records and reports
• Ungrouped data


  Raw, unorganized information
• Grouped data


  Data presented in a frequency distribution table, organized, or processed data
• Data


  Singular: datum, Plural: data (many information, known facts, figures, observations, statistics, records and reports)
• Nominal level data


  The "lowest" level of data measurement, classification has no natural order, no measurement involved, only counts, mutually exclusive and exhaustive categories with no logical order
• Nominal level data examples


  • hair color
  • gender
  • religious affiliation
• Ordinal level data


  May be arranged in some order, but differences between data values cannot be determined or are meaningless, one category is "higher" or "better" than the next one, mutually exclusive and exhaustive categories ranked according to the particular trait they possess
• Interval level data


  Includes all the characteristics of the ordinal level, plus the difference between values is a constant size, no natural zero point
• Ratio level data


  The "highest" level of data measurement, has all the characteristics of the interval level, plus the zero (0) point is meaningful and the ratio between two numbers is meaningful
• Ratio level data examples


  • Money
  • Units of production
  • Weight
  • Income
  • Number of students
• Measure of central location


  Also called measure of central tendency, refers to any measure indicating the center of a set of data arranged in either descending or ascending order, the most commonly used are mean, median and mode
• Mean


  The arithmetic mean of a set of values, the quantity commonly called the mean or the average, the sample mean is an unbiased estimator for the population mean
• Properties of the arithmetic mean

  • Every set of interval-level and ratio-level data has a mean
  • All the values are included in computing the mean
  • A set of data has only one mean, the mean is unique
  • The mean is a useful measure of comparing two or more populations
  • The arithmetic mean is the only measure of location where the sum of the deviations of each value forms the mean will always be zero
• Weighted mean


  An average in which each quantity to be averaged is assigned a weight, data elements with high weight contribute more to the weighted mean than do elements with low weight
• Median


  The middle value when the number of observations is odd, or the arithmetic mean of the two middle values when the number of observations is even, usually divides the group into two equal parts
• Median examples


  • Median of 27, 23, 29, 5, 25, 24, 22, 30, 23, 9, 26, 22, 24, 13, 26 is 24

  Median of 14, 5, 8, 3, 8, 18, 21, 25, 24, 10, 3, 4, 15, 28 is 12 (arithmetic mean of 10 and 14)
• Mode


  The value that appears most frequently, especially useful in describing an ordinal level of measurement
• Mode examples


  • In the series 84, 85, 92, 78, 65, 69, 79, 69, 78, 93, 91, 68, 75, 80, 67, the modes are 69 and 78, the median is 78, and the mean is 78.2