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34問 • 1年前
  • Jan Rick Trinidad
    • 通報

    問題一覧

  • 1

    Science of collecting, organizing, summarizing and analyzing information to draw condusions or answers question -It provides procedure in data collection, presentation, organization and interpretation to have a meaning ful idea.

    STATISTICS

  • 2

    According to Meriam Webster, it is factual information (such as measurements or statistics) used as a basis for reasoning, discussion or calculation.

    DATA

  • 3

    basically consists of organizing and summarizing data. - describes data through numerical summaries, tables and graphs.

    DESCRIPTIVE STATISTICS

  • 4

    logical process that involves generalizing from a sample to the population from which the sample was selected and assessing the reliability of such generalizations. Comparison/ Venn diagram

    INFERENTIAL STATISTICS

  • 5

    consists of ALL the members of the group about which you want to draw a condusion

    POPULATION

  • 6

    numerical index describing a charactenstic of a population

    PARAMETER

  • 7

    Come from a onginal source and are intended to answer a specific research question. can be taken by interview, mait in questionnaire, survey or experimentation

    PRIMARY

  • 8

    data taken from prenoudy recorded data internet can also be taken electronically for instance via websites.

    SECONDARY

  • 9

    characteristic of objects, people or events that does not vary.

    CONSTANT

  • 10

    characteristic of objects, people or events that take different values.

    VARIABLE

  • 11

    Vield categorical responses •words or codes that represent dass or category Ex: SR-CODE. Sss no.

    QUALITATIVE/CATEGORICAL VARIABLE

  • 12

    take on numerical values representing on amount or quantity. how much or how many

    QUANTITATIVE/NUMERICAL VARIABLE

  • 13

    Independent and dependent variable

    EXPERIMENTAL

  • 14

    Variable can stand alone

    INDEPENDENT VARIABLES

  • 15

    Variable that extremely rely on another things

    DEPENDENT VARIABLES

  • 16

    whole no values

    DISCRETE

  • 17

    decimal no.

    CONTINUOUS

  • 18

    categorical data where categories have no rankingforder

    NOMINAL LEVEL/QUALITATIVE

  • 19

    categorical data where categories have ranking or order Ex:highest educational attainment

    ORDINAL LEVEL/QUALITATIVE

  • 20

    numerical data that has no absolute zero Example: temperature

    INTERVAL LEVEL/QUANTITATIVE

  • 21

    highest (numerical data thas has an absolute 0. Ex: net weight of grains cereals

    RATION LEVEL/QUANTITATIVE

  • 22

    process of choosing/selecting individuals from population to sample.

    SAMPLING

  • 23

    using an objective chance of mechanism to choose sample the probability of selection for a sample is KNOWN

    PROBABILITY/RANDOM SAMPLING

  • 24

    there is an equal chance of selection for the samples ex: use of lottery or via random names fishball method wheel of names

    SIMPLE RANDOM SAMPLING

  • 25

    •System or pattem on choosing samples

    SYSTEMATIC SAMPLING

  • 26

    dividing the population to non overlapping groups called strata choosing sample from each strata.

    STRATIFIED RANDOM SAMPLING

  • 27

    dividing population into non-overlapping groups then randomly select a group and choose all samples within that group.

    CLUSTER SAMPLING

  • 28

    dividing population into non-overlapping groups then randomly select a group and choose all samples within that group.

    CLUSTER SAMPLING

  • 29

    sampling method where no objective chance mechanism is used. We choose sample by convenience or hazardly or taking volunteers. probability of selection is UNKNOWN.

    NON-RANDOM SAMPLING/NON-PROBABILITY

  • 30

    Sampling-choosing sample that are Conveniently available to you.

    CONVENIENCE SAMPLING

  • 31

    identifying a specific anteria or qualification before an individual can be a sample

    PURPOSIVE SAMPLING

  • 32

    Sampling-non probability counterpart of STRS

    CUOTA SAMPLING

  • 33

    relying on samples to obtain more samples.

    SNOWBALL SAMPLING

  • 34

    asking samples to volunteer to be part of the study.

    VOLUNTEER SAMPLING

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    問題一覧

  • 1

    Science of collecting, organizing, summarizing and analyzing information to draw condusions or answers question -It provides procedure in data collection, presentation, organization and interpretation to have a meaning ful idea.

    STATISTICS

  • 2

    According to Meriam Webster, it is factual information (such as measurements or statistics) used as a basis for reasoning, discussion or calculation.

    DATA

  • 3

    basically consists of organizing and summarizing data. - describes data through numerical summaries, tables and graphs.

    DESCRIPTIVE STATISTICS

  • 4

    logical process that involves generalizing from a sample to the population from which the sample was selected and assessing the reliability of such generalizations. Comparison/ Venn diagram

    INFERENTIAL STATISTICS

  • 5

    consists of ALL the members of the group about which you want to draw a condusion

    POPULATION

  • 6

    numerical index describing a charactenstic of a population

    PARAMETER

  • 7

    Come from a onginal source and are intended to answer a specific research question. can be taken by interview, mait in questionnaire, survey or experimentation

    PRIMARY

  • 8

    data taken from prenoudy recorded data internet can also be taken electronically for instance via websites.

    SECONDARY

  • 9

    characteristic of objects, people or events that does not vary.

    CONSTANT

  • 10

    characteristic of objects, people or events that take different values.

    VARIABLE

  • 11

    Vield categorical responses •words or codes that represent dass or category Ex: SR-CODE. Sss no.

    QUALITATIVE/CATEGORICAL VARIABLE

  • 12

    take on numerical values representing on amount or quantity. how much or how many

    QUANTITATIVE/NUMERICAL VARIABLE

  • 13

    Independent and dependent variable

    EXPERIMENTAL

  • 14

    Variable can stand alone

    INDEPENDENT VARIABLES

  • 15

    Variable that extremely rely on another things

    DEPENDENT VARIABLES

  • 16

    whole no values

    DISCRETE

  • 17

    decimal no.

    CONTINUOUS

  • 18

    categorical data where categories have no rankingforder

    NOMINAL LEVEL/QUALITATIVE

  • 19

    categorical data where categories have ranking or order Ex:highest educational attainment

    ORDINAL LEVEL/QUALITATIVE

  • 20

    numerical data that has no absolute zero Example: temperature

    INTERVAL LEVEL/QUANTITATIVE

  • 21

    highest (numerical data thas has an absolute 0. Ex: net weight of grains cereals

    RATION LEVEL/QUANTITATIVE

  • 22

    process of choosing/selecting individuals from population to sample.

    SAMPLING

  • 23

    using an objective chance of mechanism to choose sample the probability of selection for a sample is KNOWN

    PROBABILITY/RANDOM SAMPLING

  • 24

    there is an equal chance of selection for the samples ex: use of lottery or via random names fishball method wheel of names

    SIMPLE RANDOM SAMPLING

  • 25

    •System or pattem on choosing samples

    SYSTEMATIC SAMPLING

  • 26

    dividing the population to non overlapping groups called strata choosing sample from each strata.

    STRATIFIED RANDOM SAMPLING

  • 27

    dividing population into non-overlapping groups then randomly select a group and choose all samples within that group.

    CLUSTER SAMPLING

  • 28

    dividing population into non-overlapping groups then randomly select a group and choose all samples within that group.

    CLUSTER SAMPLING

  • 29

    sampling method where no objective chance mechanism is used. We choose sample by convenience or hazardly or taking volunteers. probability of selection is UNKNOWN.

    NON-RANDOM SAMPLING/NON-PROBABILITY

  • 30

    Sampling-choosing sample that are Conveniently available to you.

    CONVENIENCE SAMPLING

  • 31

    identifying a specific anteria or qualification before an individual can be a sample

    PURPOSIVE SAMPLING

  • 32

    Sampling-non probability counterpart of STRS

    CUOTA SAMPLING

  • 33

    relying on samples to obtain more samples.

    SNOWBALL SAMPLING

  • 34

    asking samples to volunteer to be part of the study.

    VOLUNTEER SAMPLING