Descriptive Statistics

Descriptive Statistics

1. Statictic

   • Statistic is the study of the collection, analysis, interpretation, presentation, and organization of data
     • Statistics Data
       • Is the study of data. It includes descriptive statistics and inferential statistics.
     • Survey
       • A survey is a study that is made to collect data.
     • Samples
       • A sample is a little part of a group, chosen to represent a whole group.
     • Population
       • Finite Population
         • A population is called finite if it is possible to count its individuals.
       • Infinite Population
         • Sometimes it is not possible to count the units contained in the population.
     • The use of Sampling
       • Among the various techniques adopted for reducing the bulk of certain classes of records is sampling, a method which can vary from a purely subjective choice of examples through a variety of procedures to an exact statistical process.
     • Atributes and Vriables
       • Attribute is a characteristic of an object. Attribute are closely related to variables. The variables are also often called quantitative traits are those that can be expressed by numbers.
     • Descriptive and inferential Statistic
       • Descriptive Statistics
         • Is the term given to the analysis of data that helps describe, show or summarize data in a meaningful way.
       • Inferencial Statistics
         • Inferential statistics are techniques that allow us to use samples to make generalizations about the populations from which the samples were drawn.
     • Methods of Data Collection
       • Observational study: Like experiments, observational studies attempt to understand cause and effect relationships (is not able to control).
       • Experiment: An experiment is a controlled study in which the researcher attempts to understand cause-and-effect relationship.
       • Census: A census is a study that obtains data from every member of a population.
       • Sample Survey: Is a study that obtains data from a subset of a population, in order to estimate population attributes.
     • Statistical Unit
       • A unit in a statistical analysis refers to one member of a set of entities being studies.
     • Data Collection Methods: Pros and Cons
       • Causal inference: Cause-and-effect relationships can be teased out when subjects are randomly assigned to groups.
       • Generalizability: Refers to the appropriateness of applying findings from a study to a larger populations.
       • Resources: When the population is large, a sample survey has a big resource advantage over a census.
     • Sample Selection
       • Simple random sampling
         • In a simple random sample of a given size, all such subsets of the frame are given an equal probabilitty.
       • Statified sampling
         • Where the population embraces a number of distinct categories, the fame can be organized by these categories into separate "strata".
       • Oversampling
         • In choice-based sampling, the data are satisfied on the target and a sample is taken from each stratum so than the rare target class will be more represented in the sample.
       • Cluster sampling
         • Sometimes it is more cost-effective to select respondents in groups. Sampling is often clustered by geography, or by time periods.
       • Quota Sampling
         • The population is first segmented into mutually exclusive sub-groups, just as in stratified sampling. Then judgement is used to select the subjects or units from each segment based on a specified proportion.
       • Accidental Sampling
         • Is a type of nonprobability sampling which involves the sample being drawn from that part of the population which is close to hand. That is, a population is selected because it is readily available and convenient.
       • Line-intercept sampling
         • Is a method of sampling elements in a region whereby an element is sampled if a chosen line segment, called a "transect" intersects the element.
       • Panel Sampling
         • Panel sampling is the method of first selecting a group of participants trough a random sampling method and then asking that group for information several times over a period of time. Therefore, each participants is interviewed at two or more time points.
       • Systematic sampling
         • Involves a random start and then proceeds with the selection.
     • Data Collection
       • Census
         • Is a study that obtains data from every member of a population.
       • Sample survey
         • Is a study that obtains data from a subset of a population.
       • Observational study
         • Like experiments, observational studies attempt to understand cause-and-effect relationships.
       • Registrations
         • Registers and licenses are particularly valuable for complete enumeration.
       • Questionaires
         • Forms which are completed and returned by respondents.
       • Interviews
         • Forms which are completed through an interview with the respondent
     • Ramdom numbers table
       • What are random numbers are sets of digits (i.e., 0, 1, 2, 3, 4, 5, 6, 7, 8, 9,) arranged in random order
     • Measures of Central Tendency
       • Mean: The mean is equal to the sum of all the values in the data set divided by the number of values in the data set.
       • Median: The median is the middle score for a set of data that has been arranged in order of magnitude.
       • Mode: Is the most frequent score in our data set.
     • Frequency Distribution
       • Frequency distributions show either the actual number of observations falling in each range or the percentage of observations.
     • Absolute Frequency
       • Is the number of times that a certain value appears in a statistical study. The sum of the absolute frequencies is equal to the total number appears in a statistical study.
     • Relative Frequency
       • How often something happens divided by all outcomes. Example: Your team has won 9 games from a total of 12 games played.
     • Height of children
       • Frequency Graphs
         • Histograms and bar charts are both visual displays of frequencies using columns plotted on a graph. The Y-axis generally represents the frequency count, while the X-axis generally represents the variable being measured.
     • Class Limits
       • Are the smallest and largest observation in each class. Therefore, each class has two limits: A lower and upper.
     • Class Intervals
       • Is the difference between the upper and lower class boundaries of any class.
     • Class Boundaries
       • Are the midpoints between the upper class limit of a class and the lower class limit of the next class in the sequence.