Statistics

• The study of Statistics does not merely involve knowing and memorizing
• A statistical inquiry is a designed research that provides information needed to solve a research problem.
• What distinguishes a statistical inquiry from other types of research is the use of data that have been collected and analyzed in answering the research problem.
• Population is a collection of all elements under consideration in a statistical inquiry
• Sample is a subset of a population
• The elements are the units whose characteristics will be observed and measured by the researchers in order to answer the research problem.
• Observation is a realized value of the variable
• Data is a collection of observations
• A summary measure is a single numeric figure that describes a particular feature of the whole collection.
• Parameter is a summary measure describing a specific characteristic of the population. (It is computed using population data.)
• Statistic is a summary measure describing a specific characteristic of the sample. (It is computed using sample data.)
• Applied statistics is concerned with the procedures and techniques used in the collection, presentation, organization, analysis, and interpretation of data.
• Mathematical Statistics is concerned with the development of the mathematical foundations of the methods used in applied statistics
• Descriptive statistics includes all the techniques used in organizing, summarizing, and presenting the data on hand.
• Inferential statistics includes all the techniques used in analyzing the sample data that will lead to generalizations about a population from which the sample came from.
• Qualitative variable is a variable that yields categorical responses
• Quantitative variable is a variable that takes on numerical values representing an amount or quantity
• Discrete variable is a variable which can assume finite, or at least countably infinite number of values.
• Measurement is the process of determining the value or label of the variable based on what has been observed.
• The survey method is a method of collecting data by asking people questions.
• When the data came from asking all the people in the population, then the study is called a census.
• when the data came from asking a sample of people selected from a well-defined population, then the study is called a sample survey
• The people who answer the questions in a survey are called respondents
• The questionnaire contains all the questions asked in a survey
• The treatments or factor levels are the values or categories of the explanatory variable that are being considered in the study
• The observation method is a method of collecting data on the phenomenon of interest by recording the observations made about the phenomenon as it actually happens.
• The target population is the population we want to study
• The sampled population is the population from where the sample is actually selected
• The elementary unit or element is a member of the population whose measurement on the variable of interest is what we wish to examine
• The sampling unit is the unit of the population that we select in our sample
• Before selecting the sample, the population must first be divided into non-overlapping sampling units.
• Sometimes the sampling unit is a group of more than one element
• The sampling frame or frame is a list or map showing all the sampling units in the population
• Sampling error is the error attributed to the variation present among the computed values of the statistic from the different possible samples consisting of n elements
• Non-Sampling error is the error from other sources apart from sampling fluctuation, such as measurement errors and coverage errors.
• Probability Sampling is a method of selecting a sample wherein each element of the population has a known, nonzero chance of being included in the sample.
• Non-probability sampling is a method of selecting a sample wherein some elements of the population do not have a known chance of inclusion in the sample or the chance is zero
• Systematic sampling is a probability sampling method wherein the selection of the first element is at random and the selection of the other elements in the sample is systematic by subsequently taking every kth element from the random start, where k is the sampling interval.
• Cluster sampling is a probability sampling method wherein we divide the population into nonoverlapping groups or clusters consisting of one or more elements, and then select a sample of clusters.
• Array is an arrangement of observations according to magnitude