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- 1. Statistics
- 2. Statistics <ul><li>Is a scientific body of knowledge that deals with: </li></ul><ul><ul><li>collection of data </li></ul></ul><ul><ul><li>organization or presentation of data </li></ul></ul><ul><ul><li>analysis and interpretation of data </li></ul></ul>
- 3. <ul><li>Is a statistical procedure concerned with describing the characteristics and properties of group of persons, places or things; it is based on easily verifiable facts. </li></ul>Descriptive Statistics
- 4. <ul><li>Is a statistical procedure used to draw inferences for the population on the basis of the information obtained from the sample. </li></ul>Inferential Statistics
- 5. <ul><li>Population. It is the total collection of all the elements (people, events, objects, measurements, and so on) one wishes to investigate. </li></ul><ul><li>Sample. Subgroup obtained from a population. </li></ul><ul><li>Parameter. A numerical value that describes a characteristic of a population. </li></ul>Definitions
- 6. <ul><li>Statistic. It is a numerical value that describes a particular sample. </li></ul><ul><li>Data. This are facts, or a set of information gathered or under study. </li></ul><ul><li>Quantitative Data are numerical in nature and therefore meaningful arithmetic can be done. </li></ul><ul><ul><li>Ex: age </li></ul></ul>Definitions
- 7. <ul><li>Qualitative Data are attributes which cannot be subjected to meaningful arithmetic. </li></ul><ul><ul><li>Ex: gender </li></ul></ul><ul><li>Discrete Data assume exact values only and can be obtained by counting </li></ul><ul><ul><li>Ex: number of students </li></ul></ul>Definitions
- 8. <ul><li>Continuous Data assume infinite values within a specified interval and can be obtained by measurement. </li></ul><ul><ul><li>Ex: height </li></ul></ul><ul><li>Constant is a characteristic or property of a population or sample which makes the member similar to each other. </li></ul>Definitions
- 9. <ul><li>Variable is a characteristic or property of a population or sample which makes the members different from each other. </li></ul><ul><li>Dependent. A variable which is affected by another variable. </li></ul><ul><ul><li>Ex: test scores </li></ul></ul>Definitions
- 10. <ul><li>Independent. A variable which affects the dependent variable. </li></ul><ul><ul><li>Ex: number of hours spent in studying </li></ul></ul>Definitions
- 11. Levels of Measurements <ul><li>Nominal numbers do not mean anything; they just label. </li></ul><ul><ul><li>Ex: SSS Number </li></ul></ul><ul><li>Ordinal numbers are used to label + rank. </li></ul><ul><ul><li>Ex: size of t-shirt </li></ul></ul>
- 12. Levels of Measurements <ul><li>Interval numbers are used to label + rank; do not have a true zero. </li></ul><ul><ul><li>Ex: temperature </li></ul></ul><ul><li>Ratio numbers are used to label + rank + equal unit of interval; have a true zero </li></ul><ul><ul><li>Ex: number of votes </li></ul></ul>
- 13. Target Practice <ul><li>A. Determine whether the set of data is qualitative or quantitative. </li></ul><ul><li>Models of cell phones </li></ul><ul><li>Number of subscribers to Philippine Daily News </li></ul><ul><li>Weights of 1000 packs of a brand of noodles </li></ul><ul><li>Yes or No responses to survey question </li></ul><ul><li>Telephone number </li></ul>
- 14. Target Practice <ul><li>B. Which of the following numbers is discrete or continuous? </li></ul><ul><li>Distance from town A to town B </li></ul><ul><li>Record of absent students in a class in Statistics </li></ul><ul><li>Number of customers in a restaurant </li></ul><ul><li>Number of cars parked in the basement of a building </li></ul><ul><li>Weights of all Grades 1 pupils in the Library School </li></ul>
- 15. Target Practice <ul><li>C. Identify the level of measurement: nominal(N), ordinal(O), interval(I), or ratio(R) most appropriate for each of the following data. </li></ul><ul><li>Color of the eye </li></ul><ul><li>Number of votes </li></ul><ul><li>Rank of faculty </li></ul><ul><li>Exam score </li></ul><ul><li>Temperature in Baguio last summer </li></ul>
- 16. Determining the Sample Size Slovin’s Formula: n is the sample size N is the population size e is the margin of error The margin of error is a value which quantifies possible sampling errors.
- 17. Determining the Sample Size The margin of error can be interpreted by the use of ideas from the laws of probability. In reality, it is what statisticians call a confidence interval. Sampling error means that the results in the sample differ from those of the target population because of the “luck of the draw”.
- 18. Sampling Techniques Sampling is the process of selecting samples from a given population. <ul><li>Probability Sampling </li></ul><ul><li>Non-probability Sampling </li></ul>Types:
- 19. Sampling Techniques <ul><li>Probability Sampling: Samples are chosen in such a way that each member of the population has a known though not necessarily equal chance of being included in the samples. </li></ul><ul><ul><li>Avoids biases </li></ul></ul><ul><ul><li>It provides the basis for calculating the margin of error. </li></ul></ul>
- 20. Sampling Techniques <ul><li>Simple Random Sampling: Samples are chosen at random with members of the population having a known or sometimes equal probability or chance of being included in the samples. </li></ul><ul><ul><li>Lottery </li></ul></ul><ul><ul><li>Generation of random numbers </li></ul></ul>
- 21. Sampling Techniques 2. Systematic Sampling: Samples are chosen following certain rules set by the researchers. This involves choosing the k th member of the population, with k=N/n, but there should be a random start.
- 22. Sampling Techniques 3. Cluster Sampling: is sometimes called area sampling because it is usually applied when the population is large. In this technique, groups or clusters instead of individuals are randomly chosen.
- 23. Sampling Techniques 4. Stratified Random Sampling: This method is used when the population is too big to handle, thus dividing N into subgroups, called strata , is necessary. A process that can be used is proportional allocation .
- 24. Sampling Techniques B. Non Probability Sampling: Each member of the population does not have a known chance of being included in the sample. Instead, personal judgment plays a very important role in the selection. Non-probability sampling is one of the sources of errors in research.
- 25. Sampling Techniques Types: <ul><li>Convenience Sampling: This type is used because of the convenience it offers to the researcher. </li></ul><ul><li>Quota Sampling: This is very similar to the stratified random sampling. The only difference is that the selection of the members of the samples in stratified sampling is done randomly. </li></ul>
- 26. Sampling Techniques 3. Purposive Sampling: Choosing the respondents on the basis of pre-determined criteria set by the researcher.
- 27. Data Gathering Techniques <ul><li>The Direct or the Interview Method: In this method, the researcher has direct contact with the researcher. </li></ul><ul><li>A: Clarification can be done easily. </li></ul><ul><li>D: Costly and time-consuming. </li></ul>
- 28. Data Gathering Techniques <ul><li>The Indirect or Questionnaire Method: The researcher gives or distributes the questionnaire to the respondents either by personal delivery or by mail. </li></ul><ul><li>A: Saves time and money; large number of samples can be reached. </li></ul><ul><li>D: Problem of retrieval </li></ul>
- 29. Data Gathering Techniques <ul><li>The Questionnaire (characteristics) </li></ul><ul><li>It should contain a short letter to the respondents which includes: </li></ul><ul><ul><li>a. The purpose of the survey </li></ul></ul><ul><ul><li>b. An assurance of confidentiality </li></ul></ul><ul><ul><li>c. The name of the researcher or writer of the questionnaire </li></ul></ul>
- 30. Data Gathering Techniques The Questionnaire (characteristics) 2. There is a descriptive title/name for the questionnaire. 3. It is designed to achieve objectives. 4. The directions are clear 5. It is designed for easy tabulation.
- 31. Data Gathering Techniques The Questionnaire (characteristics) 6. It avoids the use of double negatives. 7. It also avoids double barreled questions. 8. It phrases questions well for all respondents.
- 32. Data Gathering Techniques <ul><li>Types of Questionnaire </li></ul><ul><li>Open – this type has an unlimited responses </li></ul><ul><li>Closed – this type limits the scope of responses </li></ul><ul><li>Combination – this type is a combination of open and closed types of questionnaire </li></ul>
- 33. Data Gathering Techniques <ul><li>Types of Questions </li></ul><ul><li>Multiple choice – allows respondent to select answer/s from the list </li></ul><ul><li>Ranking – asks respondents ton rank the given items </li></ul><ul><li>Scales – asks respondents to give his/her degree of agreement to a statement (Likert-scale) </li></ul>
- 34. Data Gathering Techniques 3.The Registration Method: This method of gathering data is governed by laws. A: Most reliable source of data D: Data are limited to what are listed in the documents
- 35. Data Gathering Techniques 4. The Experimental Method: This method of gathering data is used to find out cause and effect relationships. A: Can go beyond plain description D: Lots of threats to internal and external validity
- 36. Presentation of Data Textual Form: Data are presented in paragraph or in sentences. This includes enumeration of important characteristics, emphasizing the most significant features and highlighting the most striking attributes of the set of data.
- 37. Presentation of Data Tabular Form: A more effective device of presenting data. 1. stem and leaf plots 2. frequency distribution table 3. contingency table
- 38. Presentation of Data Graphical/Pictorial Form: A most effective device of presenting data. 1. line graph (freq. polygon, ogive) 2. bar graph (histogram) 3. pie chart 4. pictograph 5. statistical maps

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