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問題一覧
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Science of collecting, organizing, summarizing, and analyzing information to draw conclusions or answer questions
statistics
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Provides procedure in data collection, presentation, organization, and interpretation to have meaningful idea
statistics
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Information referred to
data
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Factual information used as a basis for reasoning, discussion, or calculation
data
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Basically consist of organizing and summarizing data
descriptive statistics
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Describe 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 sample was selected
inferential statistics
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Inferential statistics is also known as?
statistical inference or inductive statistics
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Consists of all the members of the group which you want to draw conclusions
population
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Portion or part of a population selected
sample
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Numerical index describing characteristic of population
parameter
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Numerical index describing characteristic of sample
statistic
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Data that come from original source and intended to answer specific research question
primary data
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Data taken from previously recorded data
secondary data
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Characteristic of object, people that does not vary
constant
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Characteristic of object, people that csn take different values
variable
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Variables that yield categorical responses
qualitative variables
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Words of codes that represent class or category
qualitative variables
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Variables that take on numerical values representing amount or quantity
quantitative variables
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These numerical values should answer the question how much or how many
quantitative variables
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Interview
primary data
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Business periodicals
secondary data
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Government reports
secondary data
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Temperature of water
constant
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Weight of person
variable
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Financial statements
secondary data
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Variable that can stand alone
independent variable
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Extremely reliant on other variables. Cannot stand alone
dependent variable
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Quantitative variable that could take on whole numbers
discrete quantitative variable
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Quantitative variable that could take on decimal numbers
continuous quantitative variable
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Categorical data where categories have no rankings or order
nominal level
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Categorical data where categories have rankings/order
ordinal level
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Numerical data that has no absolute value
interval level variable
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Numerical data that has an absolute value
ratio level
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Process of choosing individuals from a population to a sample
sampling
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You are using an objective chance mechanism to obtain a sample
probability or random sampling
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The probability of selection for a sample is known
probability or random sampling
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There is an equal chance of selection for your samples
simple random sampling
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There is a system or pattern in choosing your sample
systematic sampling
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You are dividing the population to non overlapping groups called strata then choosing sample from each strata
stratified random sampling
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You divide the population into strata then normally 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 instead the sample is chosen by convenience
non probability/non random sampling
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We are choosing the samples conveniently available
convenience sampling
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We identify a specific criteria or qualification before an individual can be a sample
purposive sampling
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Non-probability counterpart of strs
quota sampling
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We are relying on samples to obtain more sample
snowball sampling
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You are asking your sample to volunteer themselves to be part of your study
voluntary sampling
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Eye color
nominal level
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Type of ballpen
nominal level
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Grading system
ordinal level
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Rating review in shopee
ordinal level
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Temperature
interval level
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Intelligence quotient or iq
interval level
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Exam scores
ratio level
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Number of siblings
ratio level
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Marital status
nominal level
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It describes the number of observations for each possible value of a variable
frequency distribution
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It presents the frequency and percentage for each possible value of a variable
frequency table
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Is the number of values in a specific class of frequency distribution or the number of occurrences of specific class in a data set
frequency
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Can be computed by the frequency of a class divided by the total number of values multiplied by 100
percentage
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Commonly referred to as an average or a single value that represents a data set
measure of central tendency
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Its purpose is to locate the center of a data set
measure of central tendency
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The most frequently used measure of central tendency
mean
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It is the only common measure in which all values play an equal role meaning to determine its values you would need to consider all the values of any given data set
mean
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What is the formula for mean
sum of all data values/number of data values
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Symbol used to represent the mean of a sample
x bar
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Symbol used to denote the mean of a population
mu
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Is the midpoint of the data array
median
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Middle most value
midpoint
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Data set arranged in order
data array
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True or false: if n is odd the median is the middle ranked value
true
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True or false: if n is even the median is the average of the two middle ranked value
true
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Is the value in a data set that appears most frequently
mode
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A data set only has one value that occurs
unimodal
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The data set has two values with the same greatest frequency both values are considered the mode
bimodal
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The data set have more than two modes
multimodal
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Cases when data set values have the same number frequency
no mode
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The mode is found by locating...
the most frequently occurring value
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Spread of data values from the average
measure of dispersion/ variability
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How is range computed
difference of highest and lowest value
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Describes the difference between data values and the mean
standard deviation
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Squared measure
variance
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Squared of SD
variance
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Describing the location of a value on the data array
measures of relative position
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Split the data set in 4 equal parts
quartiles
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Split the data array in 10 equal parts
deciles
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Split the data array in 100 equal parts
percentiles
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Formula for quartiles
Qk=nk/4+0.5
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Formula for deciles
Dk=nk/10+0.5
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Formula for percentiles
Pk=nk/100+0.5