問題一覧
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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
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According to Meriam Webster, it is factual information (such as measurements or statistics) used as a basis for reasoning, discussion or calculation.
DATA
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basically consists of organizing and summarizing data. - describes data through numerical summaries, tables and graphs.
DESCRIPTIVE STATISTICS
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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
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consists of ALL the members of the group about which you want to draw a condusion
POPULATION
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numerical index describing a charactenstic of a population
PARAMETER
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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
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data taken from prenoudy recorded data internet can also be taken electronically for instance via websites.
SECONDARY
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characteristic of objects, people or events that does not vary.
CONSTANT
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characteristic of objects, people or events that take different values.
VARIABLE
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Vield categorical responses •words or codes that represent dass or category Ex: SR-CODE. Sss no.
QUALITATIVE/CATEGORICAL VARIABLE
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take on numerical values representing on amount or quantity. how much or how many
QUANTITATIVE/NUMERICAL VARIABLE
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Independent and dependent variable
EXPERIMENTAL
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Variable can stand alone
INDEPENDENT VARIABLES
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Variable that extremely rely on another things
DEPENDENT VARIABLES
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whole no values
DISCRETE
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decimal no.
CONTINUOUS
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categorical data where categories have no rankingforder
NOMINAL LEVEL/QUALITATIVE
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categorical data where categories have ranking or order Ex:highest educational attainment
ORDINAL LEVEL/QUALITATIVE
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numerical data that has no absolute zero Example: temperature
INTERVAL LEVEL/QUANTITATIVE
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highest (numerical data thas has an absolute 0. Ex: net weight of grains cereals
RATION LEVEL/QUANTITATIVE
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process of choosing/selecting individuals from population to sample.
SAMPLING
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using an objective chance of mechanism to choose sample the probability of selection for a sample is KNOWN
PROBABILITY/RANDOM SAMPLING
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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
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•System or pattem on choosing samples
SYSTEMATIC SAMPLING
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dividing the population to non overlapping groups called strata choosing sample from each strata.
STRATIFIED RANDOM SAMPLING
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dividing population into non-overlapping groups then randomly select a group and choose all samples within that group.
CLUSTER SAMPLING
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dividing population into non-overlapping groups then randomly select a group and choose all samples within that group.
CLUSTER SAMPLING
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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
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Sampling-choosing sample that are Conveniently available to you.
CONVENIENCE SAMPLING
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identifying a specific anteria or qualification before an individual can be a sample
PURPOSIVE SAMPLING
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Sampling-non probability counterpart of STRS
CUOTA SAMPLING
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relying on samples to obtain more samples.
SNOWBALL SAMPLING
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asking samples to volunteer to be part of the study.
VOLUNTEER SAMPLING