FUNDAMENTAL CONCEPTS OF STATISTICS (Part 1 - The Nature of Statistics)
Indirect or Questionnaire Method.
This is one of the easiest methods of data gathering. It takes time to prepare because questionnaires need to be attractive. The content of a typical questionnaire, directions included, must be precise, clear and self-explanatory. Illustrations and pictures may be used to add clarity and attractiveness.
Direct or Interview Method.
This is one of the most effective methods of collecting original data. To obtain accurate responses, well-trained interviewers may do the interview. The interviewers can be of great help to the respondents in answering questions that the respondents cannot understand. It provides consistent and more precise information; however, it can be time-consuming, expensive and has limited field coverage.
Experiment Method.
This method is applied to collect or gather data if the investigator wants to control the factors affecting the variable being studied. An example is when the researcher aims to determine the different factors affecting the academic performance of the students such as methods or approaches used in teaching, etc. Experiments are conducted to determine the cause-and-effect relationship of certain phenomena under controlled conditions.
Telephone Interview
This method is employed if the questions to be asked are brief and few. An example is the check made on listeners to certain radio programs like asking what program his radio is turned on to. This method is used to find the most popular TV or radio programs.
Observation Method.
This method is utilized to gather data regarding attitudes, behavior, values and cultural patterns of the samples under investigation.
Registration Method.
Through this method, the respondents provide information in compliance with certain laws, policies, rules, regulations, decrees or standard practices. Data which can be collected by the registration method are as follows: marriage contracts, birth certificates, motor registrations, license of firearms, registration of corporations, real estates, voters, etc.
Inferential Statistics
demands a higher order of critical judgment and mathematical methods. It aims to give information about large groups of data without dealing with each element of these groups. It pertains to the methods dealing with making inference, estimates or prediction about a large set of data using the information gathered.
parameter
descriptive measure of the population
class average of examination, range of student scores, average salary, means of managerial satisfaction, and average return of investment.
examples of descriptive stat
Statistical knowledge
helps us use the proper methods to collect the data, employ correct analyses, and effectively present the results. It is a crucial process behind how we make discoveries in science, make decisions based on data, and make predictions.
Statistics
is a branch of mathematics which deals with the collection, presentation, analysis, and interpretation (CPAI) of numerical data which may be used for prediction or verification of relationships among variables.
Ratio Scale
is an interval scale modified to include inherent zero starting point.
Descriptive Statistics
is concerned with the gathering, classification and presentation of data and the collection of summarizing values to describe the group characteristics of the data.
Sampling
is the process or technique of drawing the sample from the population.
in economics
it determines, trends, helps financial analysts make investment decisions and determines the potential of an investment including inventory turn-over ratio of cash flow to total assets; the quick ratio which is the ratio of the difference between current assets and inventory values to current liabilities; return on assets before taxes; and controls of the quality of goods produced and many others.
Data gathering or collection
may be done through interview, questionnaires, tests, observation, registration, and experiments.
raw data
measurements that are collected from the original information. these data may be treated by statistical methods that are used to describe, to relate, or associate, and make inference, depending on the nature or purpose of the research problems on hand.
percentage, measures of central tendency and location; of variability or dispersion; of skewness and kurtosis
most used summarizing values to describe group characteristics of data
Ordinal Scale (Ranked)
not only classify items, but also give the order or ranks of classes, items or objects. The differences between data values either cannot be determined or meaningless.
hypothesis using the z-test, t-test, simple linear correlation, analysis of variance (ANOVA), chi-square, regression, and time series analysis
Commonly used inferential statistical tools or techniques are
Statistics
Generally, the term means numerical observation of any kind.
Statistics
A quantity calculated from the observations in a sample is called a _________ (sample mean, sample median, sample mode, sample variance, and sample standard deviation). Usually denoted by small English letters.
Universe
A universe is the set of all the individuals or entities under consideration.
Variable
A variable is a characteristic of interest measurable on each individual of the universe. It is a quantity which may take on several different value
Survey
1. is limited to a particular area or locality.
Parameter
A numerical characteristic of a population is called a _______. _______ of a given population are constants or fixed for that population (population mean, population variance, population standard deviation, and population size). _______ are usually denoted by Greek letters and/or capital English letters
Descriptive and Inferential Statistics
The field of statistics may be divided into two categories:
Population
a. A population is the set of all possible values of a variable. b. A population is the set of all observations made on all objects under study for a given characteristic or variable.
Sample
a. A sample is a set of observations which constitute a part of a population. b. A sample is the representative part of the population selected for the purpose of making inference about the population
statistics as science
are evident in empirical studies. Among the contributions of statistics are it aids in decision making, summarizes or describes data, helps to forecast or predict future outcomes, aids in making inferences, and helps in comparisons or establishing relationships
Interval Scale
are numbers assigned to items not only to identify and rank the objects but also measure the degree of differences between any two classes. It may lack inherent zero starting point.
Discrete or discontinuous data
are those obtained by counting (number of days, number of students, etc.). Remarks: In Statistics, although some data are discrete, they may be treated as continuous. We may have this type of data, that is, the average number of children per family in a certain barangay is 3.4.
Continuous data
are those obtained by measurements (length of a room, weight of a stone, 4 meters, 15 pounds, etc.).
Dependent variables
are those variables where the existence of the first is influenced by the occurrence of the second variable.
Independent variables
are those variables where the occurrence of the first is not relative to the existence of the second variable (for example, the number of fishermen is independent of the number of deaths in a given province).
Qualitative variables
are those which change in quality. They are rankables (kindness, temperament, loyalty, truthfulness, etc.).
Quantitative variables
are those which change in quantity. They are measurables (intelligence, height, weight, size, length, etc.).
Greek letters
are used to represent parameters
ability to make decisions about parameters without having the complete census of the population
basis for inferential statistics is the
Census
considers the national boundaey of a country
Nominal Scale (Categorical)
consists only of names, labels or categories which are used merely for identification or classification purposes.
Analysis of data
pertains to the process of extracting from the given data relevant and noteworthy information and this uses statistical tools or techniques.
μ (mu)
population mean
σ (sigma
population standard deviation
σ2
population variance
Primary data
refer to information which are gathered directly from an original source, or which are based on direct or first-hand experience (autobiographies, diaries, interviews, etc.).
Secondary data
refer to information which are taken from published or unpublished data which are previously gathered by other individuals or agencies (published books, newspapers, biographies, business reports, etc.).
Interpretation of data
refers to the drawing of conclusions or inferences from the analyzed data. This may involve the formulation of forecast prediction about a large group based on the data collected from small or representative group.
Presentation of data
refers to the organization of data into tables, graphs, charts, or paragraphs. Hence, presentation of data may be tabular, graphical, or textual.
in education
statistical techniques and methods are used to get information on enrollment, finance, physical facilities, dropout rate, proficiency level and many others
in research
statistical tools are used to test differences, effectiveness, impact, relationship, or independence of some variables.
population
the conclusions on the important characteristics apply to a large set of data
sample
the subset or a representative group of the population is called the
statistical data
took the forms of figures or birth, death, tax returns, population, frequency of failures in schools, crop yield, etc.
Roman letter
used to denote a test statistic.
Management
uses statistics in decision making and in varied aspects such as organizational behavior, labor relations, human-resource allocation, performance assessment and evaluation for the improvement of personal relation.