Introduction You may have heard of the word statistics because it is often used in almost all walks of life. We use statistics in everyday life. Political analysis would report the President’s popularity rating based on surveys conducted The DOH would announce the mortality rate due to an existing epidemic.
The average number of HS students who drops from school. The most requested song in the radio for the month. The effectivity of a new brand of detergent …… we are concerned with the data that relate to statistics.
Statistics is an essential research tool. Data and findings obtained from research are organized, summarized and analyzed using statistical procedures.
What is statistics? Is a scientific body of knowledge that deals with the collection, organization or presentation, analysis and interpretation of data. Procedures or steps: 1. collection 2. organization or presentation 3. analysis 4. interpretation
Why do we need to study statistics? Is it important in our lives? It certainly is, because statistics has many applications in various disciplines and in real life. In business – a business firm collects and gathers data or information from everyday operations. In Education – through statistical tool, a teacher can determine the effectiveness of a particular teaching method by analyzing test scores obtained by their students. In Psychology- Psychologist are able to interpret meaningful aptitude test. IQ tests and other psychological tests using statistical procedures or tools.
In politics or government – public opinion and election polls are commonly used to assess the opinions or preferences of the public for issues or candidates of interest. In entertainment – the most favorite actresses and actors can be determined by using surveys.
Two Categories Descriptive statistics – is a statistical procedure concerned with describing the characteristics and properties of a group of persons, places and things. Inferential statistics – is a statistical procedures that is used to draw inferences or information about the properties and characteristics by a large group of people, places, or things on the basis of the information obtained from a small portion of a large group.
Scales of measurement 1.Nominal scale – is used when we want to distinguish one object from another for identification purposes. We can only say that one object is different from another, but the amount of difference between them cannot be determined. We cannot tell that one is better or worse than the other. Gender. Nationality and civil status are of nominal scale.
2. Ordinal Scale – data are arranged in some specified order or rank. When objects are measured in this level, we can say that one is better or greater than the other. But we cannot tell how much more or how much less of the characteristics one object has than the other. The ranking of contestants in a beauty contest, of siblings in the family, of honor students in the class are of ordinal scale.
3. Interval scale – if data are measured in the interval level, we can say not only that one object is greater or less than another, but we can also specify the amount of difference. To illustrate: suppose maria got 50 in a math examinations while martha got 40. we can say that maria got higher than martha by 10 points.
4. Ratio Scale – the ratio level of measurement is like the interval level. The only difference is that the ratio level always starts from an absolute or true zero point. We can say that one object is so many times as large or as small as the other. Suppose Mrs. Reyes weighs 50 Kg. while her daughter weighs 25 kg. we can say that mrs reyes is twice as heavy as her daughter. Thus weight is an example of data measured in the ratio scale.
Ways of collecting or gathering data The direct or interview method The indirect or questionnaire method The registration method The experimental method
Sample Size In research, we seldom use the entire population because of the COST and TIME involved. Most researchers do not use the population in their study, instead the sample which is a small representative of a population is used. The Slovin’s formula is used.
Stratified Random sampling There are some instances whereby the members of the population do not belong to the same category, class or group. Comes from the root word strata which means groups or categories ( singular form is stratum). When we use this method, we are actually dividing the elements of a population into different categories, and then the sample are drawn or selected proportionally.
Frequency distribution table Relative frequency distribution Cumulative frequency distribution Graphical method: - bar chart - histogram - frequency polygon - pie chart - ogive
Measures of central tendency Mean Median Mode ungrouped data grouped data
Measures of variability Range Mean absolute deviation Variance Standard deviation
What functions do statistics perform in research? Statistical methods help the researcher in making his research design, particularly in experimental research. Statistical methods are always involved in planning a research project because in some way statistics directs the researcher how to gather his data.
2. Statistical techniques help the researcher in determining the validity and reliability of his research instruments. Data gathered with instruments that are not valid and reliable are almost useless and so the researcher must have to be sure that his instruments are valid and reliable. Statistics helps him in doing this.
3. statistics are used to test the hypothesis, whether his hypothesis are to be accepted or to be rejected. 4. Statistical treatment give meaning and interpretation to data.
Guidelines in the selection and application of statistical procedures Data should be organized using any or all of the following depending upon what is desired to be known or what is to be computed. (tabulation table, arrangement of scores, class (grouped) frequency distribution. When certain proportions of the population based on a certain variables such as age, height, income, etc. are desired to be known, frequency counts with their frequency percent's may be used.
3. When the typical, normal or average is desired to be known, the measures of central tendency such as the mean, median, or the mode may be computed and used. 4. When variables being studied are abstract or continuous such that they cannot be counted individually such as adequacy, efficiency, excellence, extent, seriousness ( of problems) and the like, the weighted mean may be computed and used if the average is desired to be known.
5. When the variability of the population is desired to be known, the measures of variability such as the range, variance and standard deviation may be computed and used