Expe. Psych

• Statistics


  In its plural sense, it refers to the data itself or some numerical computations derived from a set of data that are systematically collected and analyzed. In singular sense, it refers to the scientific discipline consisting of theory and methods for processing numerical information that one can use when making decisions in the face of uncertainty. In the broadest sense, "statistics" refers to a range of techniques and procedures for analyzing, interpreting, displaying, and making decisions based on data.
• Statistics is the language of science and data. The ability to understand and communicate using statistics enables researchers from different labs, different languages, and different fields articulate to one another exactly what they have found in their work. It is an objective, precise, and powerful tool in science and in everyday life
• Why do we study statistics?

  It serves as the link between a research idea and usable conclusions. Without statistics, we would be unable to interpret the massive amounts of information contained in data. Without a way to organize these numbers into a more interpretable form, we would be lost, having wasted the time and money of our participants, ourselves, and the communities we serve.
• Some Applications of Statistics

  • Determining the level of patient's satisfaction on the nursing care administered by student nurses at Central Mindanao University. Determining the distribution of the number of text messages sent per day of CMU students enrolled in Math 15. Comparing the exam results in Statistics of the different CMU colleges. Relationship of faculty status and work commitment. Prediction of the number of CMU students for the next school year 2009 − 2010.
• Descriptive Statistics


  Methods concerned with collecting, describing, and analyzing a set of data without drawing conclusions (or inferences) beyond the data.
• Inferential Statistics


  Methods concerned with the analysis of a subset of data leading to predictions or inferences about the entire set of data, that is, to generalize results beyond the data collected provided that the data collected is a part (sample) of a large set of items (population)
• Descriptive Statistics


  • Total number of CMU students that are university scholar. The CMU registrar cited statistics showing an increase number of CMU students during the past five years. If we are analyzing birth certificates, for example, a descriptive statistic might be the percentage of certificates issued in New York State, or the average age of the mother. The table shows the average salaries for various occupations in the Philippines in 1999.
• Inferential Statistics


  • A new milk formulation designed to improve the psychomotor of infants was tested on randomly selected infants. Based on the results, it was concluded that the new milk formulation is effective in improving the psychomotor development of infants.
• Universe


  The set of all entities under study, that is, the collection of things or observational units under study.
• Variable


  A characteristic observed or measured on every unit of the universe.
• Population


  The set of all possible values of the variable.
• Sample


  A subset of the population.
• Parameters


  Numerical measures that describe the population or universe of interest.
• Statistics


  Numerical measures of a sample.
• Frame


  A listing of all the elements in a population.
• Census


  The process in which information is gathered for all units in the population.
• Sample survey or sampling


  The process in which information obtained is only a part of the population.
• Qualitative variables


  Variables that yield observations by which individuals can be categorized according to some characteristic or quality. They are expressed in categories.
• Quantitative variables


  Variables that yield observations that can be measured. Numerical measure exists.
• Constant


  Variable that only assume one value.
• Discrete data


  Data that can be counted, e.g., number of patients in a hospital, number of students who obtained 1.0grade in Math15 and Math34. These data assume only a countable number of values.
• Continuous data


  Data that can be measured, e.g., systolic blood pressure, weight and height. These data result from infinitely many possible values that can be associated with points on a continuous scale in such a way that there are no gaps or interruptions.
• Nominal scale


  The lowest level of measurement and is most often used with variables that are qualitative in nature, rather than quantitative. It possesses only the property of identity. Numbers are only used to classify.
• Ordinal scale


  Possesses the property of identity and order. Can rank-order the objects to whether they possess more, less or the same amount of the variables being measured. Cannot determine how much greater or less A is than B in the attribute being measured.
• Interval scale


  Possesses the properties of identity, order and additivity but do not have the absolute zero property.
• Ratio scale


  Possesses the properties of identity, order, equality of scale and absolute zero. It is an interval scale with the additional property that its zero position indicates the absence of the quantity being measured.
• Rating scales are used frequently in psychological research. For example, experimental subjects may be asked to rate their level of pain, how much they like a consumer product, their attitudes about capital punishment, their confidence in an answer to a test question.
• Index, Subscript, Notation


  In statistics, we usually deal with group of data that result from measuring one or more variables. The data are often derived from samples and occasionally from population, but in either case it is useful to let symbols stand for the variables measured in the study. Usually most statistics books used the Roman letter and sometimes to stand for the variable(s) measured. The number of observations is also represented by N and n for population and sample, respectively. Let the symbol xi (read x sub i) denote any of the N or n values, if n values we have x1, x2, x3,..., xn assumed by a variable X. The letter i in xi which stands for any of the numbers 1, 2, 3, . . . , n is called a subscript, or index.
• Summation symbol (∑)


  A more compact way of writing the sum of a set of data values.
• Summation symbol (∑) examples

  • ∑6

  i=1 xi = x1 + x2 + x3 + ... + x6

  ∑4

  i=1 xi^2

  ∑4

  i=1 x2

  i
• Properties of summation symbol (∑)

  1. ∑n

  i=1 cxi = c∑n

  i=1 xi

  2. ∑n

  i=1 c = nc