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STATISTIC 1
44問 • 3ヶ月前
  • Desa Mae Santiago
  • 通報

    問題一覧

  • 1

    – is a branch of mathematics that deals with the collection, organization, presentation, analysis, and interpretation of data.

    Statistics

  • 2

    consist of methods for organizing, presenting, and describing data by using tables, graphs, and summary measures.

    Descriptive Statistics

  • 3

    is concerned with inferring or drawing conclusions about the population based from pre-selected elements of that population.

    Inferential Statistics

  • 4

    refer to the fundamental quantities that do not change in value

    Constant

  • 5

    are quantities that may take anyone of a specified set of values.

    Variables

  • 6

    are non-measurable characteristics that cannot be assume a numerical value but can be classified into two or more categories.

    Qualitative (Categorical) Variables

  • 7

    are those quantities that can be counted with your bare hands, can be measured with the use of some measuring devices, or can be calculated with the use of mathematical formula.

    Quantitative (Numerical) Variables

  • 8

    are variables that are countable and can assume only a certain values with no intermediate values.

    Discrete Variables

  • 9

    are variables that can assume any value over a certain interval or range, and we cannot count these variables.

    Continuous Variables

  • 10

    are numbers or measurements that are collected as a result from observation, interview, questionnaire, experimentations, test and so forth.

    Data

  • 11

    is a set of data that have been processed and presented in a form suitable for human interpretation

    Information

  • 12

    is a first-hand information that is obtained usually by means of personal interview and actual observation.

    Primary Source

  • 13

    is taken from other’s works, news reports, and readings.

    Secondary Source

  • 14

    applies to the data can be ranked and for which all arithmetic operation can be done, it also takes into account the interval size and ratio of two related quantities, which are usually based on a standard measurement

    Ratio Scale

  • 15

    applies to data that can be ranked and for which we can find the difference between two values can be calculated and interpreted

    Interval Scale

  • 16

    applies to data that are divided into different categories that can be ranked

    Ordinal Scale

  • 17

    applies to data that are into different categories and these are used only for identification purposes.

    Nominal Scale

  • 18

    – is a person-to-person interaction between an interviewer and an interviewee.

    Direct or Interview Method

  • 19

    – is an alternative method for the interview method. Written responses are obtained by distributing questionnaires to the respondents through mail or hand-carry

    Indirect or Questionnaire Method

  • 20

    – is enforced by private organizations or government agencies for recording purposes

    Registration Method

  • 21

    – is a scientific method of investigation that makes possible use of all senses to measure or obtain outcomes/responses from the object of study.

    Observation Method

  • 22

    – is used when the objective is to determine the cause and effect of a certain phenomenon under some controlled conditions.

    Experimentation

  • 23

    consists of all elements – individuals, items, or objects – whose characteristics are being studied

    Population

  • 24

    is a portion of the population selected for study.

    Sample

  • 25

    is any numerical value describing a characteristic of population.

    Parameters

  • 26

    in determining the Sample Size The sample size can be obtained by the formula

    Slovin’s Formula

  • 27

    is a vital tool if the information gathered would be used for administrative purposes and if it is local or national concern.

    Complete Enumeration or Census Taking

  • 28

    is the most commonly used sampling technique in which each member in the population is the given as equal chance of being selected in the sample.

    Random Sampling

  • 29

    is a method of collecting a small portion of the population by which not all the members is the population are given the chance to be included in the sample

    Non-random Sampling

  • 30

    – means that each member of the population has an equal chance of being selected and included in the sample.

    Equiprobability

  • 31

    – means that the chance of one member being drawn does not affect the chance of the other member

    Independence

  • 32

    – involves certain restrictions intended to improve the validity of the sampling. This design is applicable only when the population being investigated requires homogeneity.

    Restricted Random Sampling

  • 33

    is considered the best random sampling design because there were no restrictions imposed and every member in the population has an equal chance of being included in the sample.

    Unrestricted Random Sampling

  • 34

    This is done by simply writing the names or numbers of all the members of the population in the small rolled pieces of paper which are later placed in a container.

    Lottery or Fishbowl Sampling

  • 35

    – this method of sampling is done by taking every kth element in the population. It applies to a group of individuals arranged in a waiting line or in a methodical manner.

    Systematic Sampling

  • 36

    – when the population can be partitioned into several strata or subgroups, it may be wiser to employ the stratified technique to ensure a representative of each group in the sample

    Stratified Random Sampling

  • 37

    – when the population is grouped into more or less homogeneous classes, that is, different groups but with a relatively common characteristic, then can be sampled independently by taking equal number of elements from each stratum.

    Simple Stratified Random Sampling

  • 38

    – In some cases, the characteristics of the population is such that the proportions of the subgroups are grossly equal. The Stratified Proportional Random Sampling – In some cases, the characteristics of the population is such that the proportions of the subgroups are grossly equal. The

    Stratified Proportional Random Sampling

  • 39

    – This method is an extension or a multiple application of the stratified random sampling technique. The number of stages depends on the number of population and the sample size needed in the survey

    Multi-stage or Multiple Sampling

  • 40

    – Also referred as non-random or non-probability sampling. It plays a major role in the selection of a particular item or in making decisions in the cases of incomplete responses or observation. This is usually based on a certain criteria laid down by the researcher or his adviser.

    Judgement or Purposive Sampling

  • 41

    – This is a relatively quick and inexpensive method to operate since the choice of the number of persons or elements to be included in a sample is done at the researcher’s own convenience or preference and is not predetermined by some carefully operated randomizing plan.

    Quota Sampling

  • 42

    – referred to as an area sampling because it is usually applied on a geographical basis. The population is group into cluster or small units, e.g., blocks or districts, in city or municipality.

    Cluster Sampling

  • 43

    – this design is applied to those samples which are taken because they are most available.

    Incidental Sampling

  • 44

    – this method has been widely used in television and radio programs to find out opinions of TV viewers and listeners regarding a controversial issue.

    Convenience Sample

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    問題一覧

  • 1

    – is a branch of mathematics that deals with the collection, organization, presentation, analysis, and interpretation of data.

    Statistics

  • 2

    consist of methods for organizing, presenting, and describing data by using tables, graphs, and summary measures.

    Descriptive Statistics

  • 3

    is concerned with inferring or drawing conclusions about the population based from pre-selected elements of that population.

    Inferential Statistics

  • 4

    refer to the fundamental quantities that do not change in value

    Constant

  • 5

    are quantities that may take anyone of a specified set of values.

    Variables

  • 6

    are non-measurable characteristics that cannot be assume a numerical value but can be classified into two or more categories.

    Qualitative (Categorical) Variables

  • 7

    are those quantities that can be counted with your bare hands, can be measured with the use of some measuring devices, or can be calculated with the use of mathematical formula.

    Quantitative (Numerical) Variables

  • 8

    are variables that are countable and can assume only a certain values with no intermediate values.

    Discrete Variables

  • 9

    are variables that can assume any value over a certain interval or range, and we cannot count these variables.

    Continuous Variables

  • 10

    are numbers or measurements that are collected as a result from observation, interview, questionnaire, experimentations, test and so forth.

    Data

  • 11

    is a set of data that have been processed and presented in a form suitable for human interpretation

    Information

  • 12

    is a first-hand information that is obtained usually by means of personal interview and actual observation.

    Primary Source

  • 13

    is taken from other’s works, news reports, and readings.

    Secondary Source

  • 14

    applies to the data can be ranked and for which all arithmetic operation can be done, it also takes into account the interval size and ratio of two related quantities, which are usually based on a standard measurement

    Ratio Scale

  • 15

    applies to data that can be ranked and for which we can find the difference between two values can be calculated and interpreted

    Interval Scale

  • 16

    applies to data that are divided into different categories that can be ranked

    Ordinal Scale

  • 17

    applies to data that are into different categories and these are used only for identification purposes.

    Nominal Scale

  • 18

    – is a person-to-person interaction between an interviewer and an interviewee.

    Direct or Interview Method

  • 19

    – is an alternative method for the interview method. Written responses are obtained by distributing questionnaires to the respondents through mail or hand-carry

    Indirect or Questionnaire Method

  • 20

    – is enforced by private organizations or government agencies for recording purposes

    Registration Method

  • 21

    – is a scientific method of investigation that makes possible use of all senses to measure or obtain outcomes/responses from the object of study.

    Observation Method

  • 22

    – is used when the objective is to determine the cause and effect of a certain phenomenon under some controlled conditions.

    Experimentation

  • 23

    consists of all elements – individuals, items, or objects – whose characteristics are being studied

    Population

  • 24

    is a portion of the population selected for study.

    Sample

  • 25

    is any numerical value describing a characteristic of population.

    Parameters

  • 26

    in determining the Sample Size The sample size can be obtained by the formula

    Slovin’s Formula

  • 27

    is a vital tool if the information gathered would be used for administrative purposes and if it is local or national concern.

    Complete Enumeration or Census Taking

  • 28

    is the most commonly used sampling technique in which each member in the population is the given as equal chance of being selected in the sample.

    Random Sampling

  • 29

    is a method of collecting a small portion of the population by which not all the members is the population are given the chance to be included in the sample

    Non-random Sampling

  • 30

    – means that each member of the population has an equal chance of being selected and included in the sample.

    Equiprobability

  • 31

    – means that the chance of one member being drawn does not affect the chance of the other member

    Independence

  • 32

    – involves certain restrictions intended to improve the validity of the sampling. This design is applicable only when the population being investigated requires homogeneity.

    Restricted Random Sampling

  • 33

    is considered the best random sampling design because there were no restrictions imposed and every member in the population has an equal chance of being included in the sample.

    Unrestricted Random Sampling

  • 34

    This is done by simply writing the names or numbers of all the members of the population in the small rolled pieces of paper which are later placed in a container.

    Lottery or Fishbowl Sampling

  • 35

    – this method of sampling is done by taking every kth element in the population. It applies to a group of individuals arranged in a waiting line or in a methodical manner.

    Systematic Sampling

  • 36

    – when the population can be partitioned into several strata or subgroups, it may be wiser to employ the stratified technique to ensure a representative of each group in the sample

    Stratified Random Sampling

  • 37

    – when the population is grouped into more or less homogeneous classes, that is, different groups but with a relatively common characteristic, then can be sampled independently by taking equal number of elements from each stratum.

    Simple Stratified Random Sampling

  • 38

    – In some cases, the characteristics of the population is such that the proportions of the subgroups are grossly equal. The Stratified Proportional Random Sampling – In some cases, the characteristics of the population is such that the proportions of the subgroups are grossly equal. The

    Stratified Proportional Random Sampling

  • 39

    – This method is an extension or a multiple application of the stratified random sampling technique. The number of stages depends on the number of population and the sample size needed in the survey

    Multi-stage or Multiple Sampling

  • 40

    – Also referred as non-random or non-probability sampling. It plays a major role in the selection of a particular item or in making decisions in the cases of incomplete responses or observation. This is usually based on a certain criteria laid down by the researcher or his adviser.

    Judgement or Purposive Sampling

  • 41

    – This is a relatively quick and inexpensive method to operate since the choice of the number of persons or elements to be included in a sample is done at the researcher’s own convenience or preference and is not predetermined by some carefully operated randomizing plan.

    Quota Sampling

  • 42

    – referred to as an area sampling because it is usually applied on a geographical basis. The population is group into cluster or small units, e.g., blocks or districts, in city or municipality.

    Cluster Sampling

  • 43

    – this design is applied to those samples which are taken because they are most available.

    Incidental Sampling

  • 44

    – this method has been widely used in television and radio programs to find out opinions of TV viewers and listeners regarding a controversial issue.

    Convenience Sample